Controlled agricultural systems and methods of managing agricultural systems
Granted 22 Jul 2025 · 12 office actions
Assignee: Fluence Bioengineering, Inc.
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Attorney: Attorney · Log in to unlock
Inventors: Marek Burza, Norbert Haas, Guido Angenendt, Norbert Magg +2 · Examiner: Sujay Koneru · AU 3624 · TC 3600
Life of the application
19 dated eventsDescription
81 parts›CROSS REFERENCE TO RELATED APPLICATIONS
This patent application is a continuation of U.S. patent application Ser. No. 16/275,476, entitled “Controlled Agricultural Systems and Methods of Managing Agricultural Systems,” filed Feb. 14, 2019, which is hereby incorporated by reference in its entirety.
›INTRODUCTION · 1 of 7
The present disclosure relates to a Controlled Agricultural System, an Agricultural Light Fixture for use in a Controlled Agricultural System and a Method for Agricultural Management.
Agriculture has been a success story for thousands of years. Technical improvements, from the very first ploughshare to today's state of the art harvesting machines, from the early use of minerals and manure by Egyptians, Romans, and Babylonians to today's tailor-made fertilizers, from early plant breeding to genetic engineering, farming culture allowed for a steady increase of the harvest. In spite of these extensive changes, one underlying principle remained the same, the plant growth was ever since and still is today driven by the natural sunlight. This success story, which began at the end of the ice age, was about
bringing the plants to the light.
The story of the present application is about
bringing the light to the plants.
It is even more about designing not only the light, but the whole environment of the farm around the plants. As far as the plants have been adapted to the natural environment by breeding and genetic engineering in the past, the present approach is to customize and adapt the farm to the specific needs of the plants. One important enabler for moving agriculture indoors is the energy efficiency of state of the art light sources.
While the energy consumption of artificial lighting has been lowered continuously, in particular driven by LED technology, traditional farming is facing more and more limits. There are not only the disadvantages of monocultural farming, over-fertilized and depleted soils, but there is also an excessive use of fuel by the large harvesting machines on the giant fields. Furthermore, this decentralized crop production implies long transport routes and world-wide shipping, with a respective impact on the food quality and the ecological footprint.
From this point of view, it is again climatic change that is driving a transition. In traditional farming, irrigating agricultural land requires enormous amounts of water, particularly in view of increasing periods of drought. Apart from that, people are moving to cities with an ever more growing distance from field to fork. In this respect, going indoors and in particular vertical farming allows for a production of high-quality food close to the consumer.
With plants being organic goods having very specific needs, a farm or agricultural system discussed here can have a quite different design and setup in detail, for instance depending on the type and size of the plants grown, but also on the location of the farm (e. g. vertical farm in a city) or other local requirements.
The embodiment of claim 1 relates to an agricultural system or farm with processing lines for growing plants. Therein, a first processing line is configured to move a first plurality of plants through the agricultural system along a route and to apply a first growth condition to the first plurality of plants to satisfy a first active agent parameter for the first plurality of plants. An active agent can for instance be a pharmaceutical ingredient, see the element “Medical Certificates” in detail.
Embodiments relating to the functionality of the farm as a whole are described in Chapter I “System Setup”. The farm, in particular a fully automated farm, can manage the entire growth system, applying not only a customized illumination to the plants (light recipes), but even customized environmental conditions (growth recipes) and solutions for maintaining or restoring plant health, see Chapter II “Plant Health/Growth” and Chapter III “Light/Growth Recipe”.
Thinking about the starting point again, bringing the light to the plants, the embodiments of Chapter IV “Luminaire” give a more detailed view of a possible light source and fixture setup in the farm.
A highly automated farm or agricultural system allows not only for intelligent solutions inside the farm, but also for an enhanced linkage of the farm to the outside world.
From this point of view, the farm is one element in a supply chain. Amongst others, electrical energy is one of the most important ingoing goods, which is described in detail in Chapter V “Smart Grid”, particularly the interaction between a controlled agricultural system and a smart grid power supply.
Further, an automated farm can also enable an alignment with downstream entities of food industry, in particular food producers. In simple words, exactly that crop (specific taste or nutrient content or the like) required in a food fab for processing a certain lot can be grown in the farm.
Finally, customers can address their requests for customized plants to the farm, which can be preprocessed and fed into the digital supply chain of the agricultural system. The customer can monitor the growth of the customized plants by means of information on the respective growth stages provided by the farm to the customer. Such interaction between farm and customer is described in more detail in Chapter VI “Customer Interaction”.
System Setup
The elements of the disclosure discussed in this chapter “System Setup” relate to the setup and functionality of the farm as a whole.
A major risk for farmers and food producers is a crop damage or even total failure, which might end up in a total economic loss. Even though going indoors can reduce the risk of for instance a storm damage, other hazards remain, as for example an infection of the plants with fungi or diseases. One major, though not the only, path of infection can be the interaction with an operating personnel bringing for instance spores from the environment outside into the farm. This can be one reason why a widely or even fully automated farm is advantageous.
Therein, the automatization in farming is hardly comparable to the production process optimization known from industrial goods. Apart from various plant specific needs, these “organic goods” change their morphology and size during production. To consider this, the element “Resizable Growth Area” proposes a growth area adjustable in size. The distance between the individual growth locations can be adapted based on the size of the plants grown there, allowing for a compact arrangement and efficient illumination at the beginning of the growth cycle and sufficient space as well as efficient illumination for the plants at the end thereof. In another aspect of “Resizable Growth Area” (but also in “Hydroponics” or “Horticulture Processing Line”, see below), the growth area can be moved through the farm, wherein at different locations different illumination setups are provided, which are perfectly adapted to the actual size of the growth area at the respective location.
›INTRODUCTION · 2 of 7
One way of moving plants through the farm is described in “Hydroponics”, showing an assembly-line perfectly adapted to the specific needs of plants. In this case, the growth locations can be trays floating on a waterway. Likewise, the transportation through the farm, for instance along different illumination areas adapted to the respective growth stage, can be combined with an inherent water or also nutrient supply in the waterway. In case of an infection or other abnormality, detected for instance by a sensor device (e.g. camera), the respective growth tray can be unloaded from the waterway to a specific treatment location, as discussed in “Horticulture Processing Line” in detail.
The specific treatment location can be comparable to a quarantine area, which can further reduce the interaction of an operating personnel at the standard processing line and the risk of a contamination. As an alternative to the waterway, the trays with the seeds or plants can also be moved on rails or elevators along the standard processing line (but also by transportation cars or moving arms or robots in general).
Even though moving the plants through the farm may initially cause a certain effort, this invest pays off when the different locations or zones of the farm are highly customized regarding the specific growth stage. A perfect illumination setup emits only spectral portions required in the specific growth stage (spectral customization), so, ideally, all photons will hit the plants (geometrical customization). In the long run, this optimization of the energy footprint pays off. A method or tool for planning a highly automated farm is described in “Light Recipes and Workflow”. As mentioned already, the setup of a sensor device or array can be crucial for the automatization, for instance to detect infected plants and trigger their unloading or treatment. An optimal arrangement or distribution of the sensors in a farm can be achieved by the method described in “Measuring Patterns”.
In general, the plant production, as described for instance in “Hydroponics” or “Horticulture Processing Line” can use plant health detection systems as for instance described in “Disease & Pest Control”, “Prophylaxis”, “Discolored Spots Detection” and/or light treatments as for instance described in “Light Guides”, “Temperature Control”, “Fungi Growth Inhibition”. The speed of the production may even be adapted to allow for a proper sensing or treatment of the plants. Regarding a proper function of the light fixtures, in particular in the long run over their lifetime, data obtained according to the method described in “Failure Detection” is helpful. The approach described there can also reduce human interaction and the risk of infection thus.
Ideally, the conditions in the farm or different zones thereof are customized to the specific needs of the plants in the respective growth stages. This customization can be supported or achieved by various sensor measurements. Therein, feedback loops can be implemented so that the plants but also the sensors themselves are monitored. In case of an error or extreme deviation from a predefined value or interval, the respective location or zone of the farm, possibly also the farm as a whole, can switch into a kind of preservation mode. There, the illumination, temperature, humidity and other important factors can be set to a point, which keeps the plants in a most comfortable condition without losing quality until the error (defect sensor or actual problem in the farm) is eliminated. As mentioned, avoiding a crop failure, a reduction in crop quality or a reduced harvested biomass are a primary objectives.
Plant Health/Growth
The elements of the disclosure discussed in this chapter “Plant Health/Growth” addresses the health and growth of plants.
While plants are growing, ideally in line with dedicated growth recipes, it is advantageous to monitor their growth and health status and even predict the yield. In case any problems are detected, measures should be taken quickly.
Agricultural Facilities, particularly horticultural facilities such as greenhouses are not completely shielded from the external surroundings. Thus, pathogens or pests may occasionally be introduced or released in a horticultural farm, for example via the ventilation system, the watering and drainage removal system or when introducing seeds and germ buds. Additionally, humans or machines deployed from the outside into the facility, for example, automated guided agricultural robots, may introduce pests into a greenhouse. Therefore, it is important to detect stress or diseases of plants at an early stage, especially in a closed environment like a vertical farm, where diseases can spread easily. Then, these critical conditions may be countered by way of appropriate measures (e.g., pesticides) in order to contain the outbreak.
It would be advantageous if there were no outbreak of diseases at all in the first place or if pests were not given the opportunity at all in the first place to spread. The element “Prophylaxis” of the disclosure describes a controlled agricultural system that is able to detect conditions that may be critical to the health of the plants and, optionally, suggests appropriate countermeasures.
Diseases or stress can be detected, for example, by color changes of the leaves or modifications of the fluorescence of the chlorophyll system, measurement of leaf reflectivity and/or false color imaging.
Particularly, diseases and stress, e.g. caused by temperature, salinization, drought, can lead to changes in morphological leaf-parameters. Such changes may comprise inclination of the leaves, form of the leaves (leaves will roll-up in case of stress, leaf wilting) or symmetry of the leaves (e.g. a damaged leaf will lose its symmetry) or necrosis, caused by fungi or viruses. The element “Stress Detection” of the disclosure describes a stress detection based on leaf parameters.
Different kinds of diseases or stress can cause different symptoms at a plant, for example on plant leaves, petals, stem or roots. Some can lead to a reduced growth of the plant, others, like the Tobacco mosaic virus, which can infect tobacco, pepper, tomato and cucumber, mainly cause “mosaic”-like mottling and discoloration on the leaves. Causes of discolorations, depending on plant type, can for example be caused by lack of nutrients or lack of chemical elements like Nitrogen (N), Phosphor (P), Potassium (K), Sulfur (S), Manganese (Mn), over-supply of nutrients, too much light, too rapid temperature changes, lack of air circulation, too dry air, too much irrigation, bacterial and virus infestation causing for example bacterial blight and bacterial wilt, soil contamination, soil temperature and many others. In addition to discoloration effects, plant leaves can develop holes.
›INTRODUCTION · 3 of 7
Therefore, cameras may be used to observe plants and detect color changes that could be associated with diseases, i.e. when the discolored parts have changed from their naturally provided colors (according to their actual growth stage) to a changed color impression, in other words when they have become discolored. Discolorations can affect only parts or small segments of a plant body (stem, petals, and leaves) or greater areas.
However, some of these color changes, particularly in an early stage of a disease, only affect small parts of the leaves, or the contrast between the discolored part and the normal colored part is small, thus making it easy to overlook the discolored areas. The element “Discolored Spots Detection” of the disclosure targets to intensify the contrast between discolored and normal colored parts of a plant.
Furthermore, some color changes (discoloration) signal a next stage of ripening, e.g. the change of color in fruits. For instance, tomatoes discolor from green to red while ripening, eventually triggering harvesting.
In any case, if plants are affected by diseases (by viruses, bacteria or fungi) or pests (such as spider mites or aphids), a quick reaction is desirable so that the disease and/or the pests cannot spread any further. Therefore, it would be advantageous if an outbreak of a plant disease could be detected in a very early stage. The element “Disease & Pest Control” of the disclosure proposes to calculate a probability whether the plants have been or will be affected by pests or diseases based on measured plant parameters.
Furthermore, it would be advantageous to have precise and early yield and harvesting time prediction at one's disposal.
Since plant health and plant growth can be influenced by several parameters like light intensity (photon flux), light spectrum, nutrients or temperature it is important to control at least the most relevant parameters. Especially when experimenting with new settings of those parameters, a fast feedback about the plant growth, i.e. the morphological parameters, is necessary. Plant growth can mean the height of the plant, the size and number and orientation of the leaves, the diameter of the plant, the plant morphology, and the height of the Apikalmeristem etc.
However, even when the parameters to grow plants in an agriculture system are set, a regular control whether the plants are growing as expected is necessary, as undetected changes in the parameters, diseases or pests can affect the plant growth. It would also be beneficial to track plant growth data or growth indicators continuously, by day and night, and correlate the data to other external parameters like temperature, nutrients, photon flux, applied spectra, etc.
The element “Yield Prediction” of the disclosure proposes a yield prediction for flowering plants by detecting the number of plants and considering the ripening probability.
Plants can be affected by several diseases, some of them caused by fungi. Therefore, it would be advantageous if growth of fungi could be inhibited automatically. The element “Fungi Growth Inhibition” of the disclosure describes a controlled agricultural system configured for applying a fungi prevention illumination.
Monitoring the health and growth stage of ideally each individual plant cultivated in agricultural facilities like greenhouses and vertical farms usually requires appropriate sensors, in some embodiments/implementations covering the entire cultivated area.
Therefore, it would be advantageous to be able to equip agricultural facilities in a sufficient, yet economical manner. The element “Sensor Retrofit” of the disclosure describes how to make use of already existing equipment for conducting the sensor measurements in the necessary extent.
Furthermore, it would be advantageous to have a flexible sensor system for measuring the morphological or growth indicative parameters, which does not contain mechanically moving parts, because it is difficult to move across the plants, particularly in a vertical farm with stacked shelves. The element “LiDAR Plant Surveillance” of the disclosure describes using LiDAR for 3D plant surveillance, commissioning the system.
For detecting plant diseases or pests, the sensing of relevant parameters is essential. The controlled agricultural system is configured to be able to analyze the measured parameters and infer a disease or pest. Furthermore, the controlled agricultural system may also be configured to be able to predict the yield based on measured parameters. Some of the parameters that can be measured are:
Leaf Area Index (LAI) (lowering of LAI can give a hint to loosing leaves by a disease) Chlorophyll fluorescence (stress detection due to wormholes or fungi/virus/bacterial infection) Shape of leaves (e.g. wormhole) Coloration of leaves (e.g. spots, necrosis, mildew, veins, rust, browning and yellowing) Leaf and ambient temperature and humidity (ambient and within the crops); humidity and temperature help to calculated the dew point. If the temperature is below the dew point, there is a high risk of water condensation on plants promoting growth of diseases Substrate moisture (substrate includes, soil, rock wool, perlite etc.) and temperature Dissolved oxygen in NFT (nutrient film technique), Deep water systems etc. EC (Electric Conductivity) and pH Value (salinity and acidity of substrate or nutrient solution) Microclimate Plant parameters like: Plant height, Leaf area, number of flowers and/or fruits Leaf thickness (if possible with a 3D scanner) The NDVI (Normal density vegetation index) determines the density of green on a patch of land
Chlorophyll strongly absorbs visible light 400-700 nm Cell structure strongly reflects near infrared (NIR) 700-1100 nm Healthy vegetation absorbs visible light and reflects large portion of NIR Unhealthy vegetation reflects more visible light and less NIR In case of bad vegetation the reflected NRI or the NDVI is close to zero In case of good vegetation the reflected NRI or the NDVI is close to 0.8
›INTRODUCTION · 4 of 7
The CRI (Carotenoid reflectance Index) determines the concentration of carotenoids in plants
Weakened vegetation contains higher concentration of carotenoids, the index is thus a measure of stressed vegetation Higher CRI1 values mean greater carotenoid concentration relative to chlorophyll CRI2 uses a modified calculation of CRI which provides better results in areas with high carotenoid concentration Value Index for CRI ranges from 0 to >15
Chlorophyll index Anthocyanin index Water Index Volatile compounds released by plants to signal stress (pests, etc.)
Some of the sensors, which can be used in the controlled agricultural system are:
Optical sensors Combination of camera and IR laser Stereo camera system Kinect system and other depth sensing cameras (relatively simple and cheap) RGB Camera (with removing the IR-filter, we also could increase the spectrum which is seen by the camera) High Resolution camera (for detecting small spots of rust/bugs/aphids etc.) Multispectral camera Camera-based motion detector Gas chromatography (detection of volatile compounds) Environmental sensors (Capacitive sensors. E.g.):
Temperature Humidity Leaf temperature VPD (Vapor pressure deficit) Substrate moisture Substrate temperature EC and pH-Value Velocity
Sensor to track nutrients (macro and micro elements)
The time interval between measurements depends on the kind of sensor. Environmental factors should be tracked every minute. Measurements with a camera systems for disease detection can be done 3-5 times per day. For example, mildew can occur over night.
Furthermore, the triggering of a measurement can be dependent on signals/events/levels/thresholds from other sensors (e.g. to cross-check/confirm detection by other means, or make the detection more specific).
One manner to detect the growth stage of plants and to detect infected plants is by using the BBCH codes (BBCH=Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie), which are available for some major crops like tomatoes, leafy greens, etc. The BBCH Codes describe the development stage with a number and provide some general drawings how it looks like. This code provides means to distinguish between different stages, discriminate the optimum of respective stage, and gives guidance with regard to disease detection and yield prediction.
Data can be collected and stored locally and/or in the cloud, i.e. the global internet network. In some embodiments/implementations, the data is transferred wireless (e.g. radio, via light) to the computing device of the controlled agricultural system und then processed, to be shown at the dashboard in the typical units (e.g. temperature ° C., rel. humidity %, absolute humidity g/m 3 , etc.), but also wired data transfer can be an option.
For big data packages, e.g. images (still or even video) the data processing in the edge, i.e. directly at the sensors, may be preferred (Edge Computing). This way, only processed and usually reduced data streams are transferred to the computing device of the controlled agricultural system for storage and analysis.
In any case, the data may be transformed in values according to the metric system or systems used in other countries (like the imperial system). The data may be processed first to render a space-resolved mapping. For example, if five sensors for temperature measurements are distributed in an area of 1 ha, the average value of the temperature may be compute as well as a kind of a temperature map for the greenhouse. Such map data can be 2D or also 3D as a point cloud. Especially if data for tracking plant growth is collected by a moving robot, a variety of sensors, including temperature sensors, can easily be added to the robot or any other automated vehicle. Furthermore, derived parameters may be calculated from measured values, for example the dew point, which is derived from temperature and humidity.
Another way to process the data could be to estimate the relative number of plants affected, like approx. 65% of your plants are infected, e.g. by detecting a necrosis or the infection with a fungi.
Most of the pre-processing may also be offloaded to the cloud—this option can advantageously allow:
to process the data in bulk; lower the costs of a sensor unit (if processing consumes processing power); potentially extend the battery life (if pre-processing consumes battery power); lower the costs of data transmission (if pre-processing leads to generating additional information); keeping original, unprocessed data (raw data) in the cloud may open up possibilities for deriving other values later, which might be closed off by pre-processing.
The data can be stored in the “original” or “raw” format or in a processed format. For example, images can be stored (raw data) or the analyzed information retrieved by analyzing the image, e.g. that x % of the plants are affected by a certain disease (processed data). Storing the original picture can be useful in case the algorithm is improved and certain values need to be re-calculated.
The data analysis may include calculating averages and relative values (percentages) and a combination of different sensor data (sensor fusion).
The data may also be manually and/or automatically annotated, e.g. what crop species was grown, when and where a disease/pest occurred. Then the controlled agricultural system may be configured to apply machine learning/AI to learn automatically the conditions for detection of the stressors or disease causing conditions.
Reference data for the comparison with measured data and subsequent analysis of the result can be generally available reference data (i.e. some generic data and not data generated at the particular agricultural system), particularly as an initial step. In the next steps, the controlled agricultural system may be configured to start using historical on-site data, for example, data from one of the previous years.
The collection of reference data may not only include specific values, but also a range of values (min., max.) including a plausibility-check of the limit values. For example, a completely unrealistic value of 5 kg for the weight of a tomato would be excluded. Update of new data, which leads to a more precise calculation process, can be provided online via cloud. It can also be possible, that growers with the same crop actively decide to upload their data to the platform connected to the controlled agriculture system. The data may be used anonymously.
›INTRODUCTION · 5 of 7
The measured data may be analyzed periodically, in real-time and/or dependent on what the customer is willing to pay.
The controlled agriculture system may be configured to inform the grower if a certain threshold (min. or max. value) of a critical parameter is reached or if, for example, a certain percentage of leaves is affected. The trigger for detecting or verifying a disease may also be a certain combination of environmental factors like EC or pH values. The trigger may also be provided by a trained AI system. The system might continue to learn while used, e.g. by supervised learning. In this case it may be beneficial to include a feedback-loop between the system and the operator to train and improve the system. To this purpose, the operator may feed back to the system whether he/she confirms or dismisses a potential issue flagged by the system.
Data storage, retrieval and processing may be managed on-site or by means of cloud-computing services, which enable on-demand access to a shared pool of computing resources (servers, applications, data, storage, processing) that can be rapidly provisioned and released via the Internet, e.g. Platform as a Service (PaaS), Software as a Service (SaaS).
Light/Growth Recipes
A vision behind the elements of the disclosure discussed in this chapter is a farm that manages the entire growth system. It can not only apply light recipes, namely a specific illumination based on the growth status, but also adjust further growth conditions. Apart from the illumination, respective control programs of the farm can for instance apply the required irrigation, fertilization, fertigation and/or plant movement.
Thinking about bringing the light to the plants, a light recipe can even go a step further. Beyond mimicking the sunlight, it can be about tailoring the illumination to a specific type of plant, in terms of the intensity and spectral composition. Different illumination setups can stimulate or trigger a difference in growth or the creation of certain ingredients (for instance primary and secondary metabolites). Even the taste or vitamin content of the crop can be influenced via the light recipe. In “Flexible growth”, the light or growth recipe is for instance used for delaying or speeding up the harvesting time to meet new target values arising during the production of the plants, namely while plants are already growing. Such target values can for instance be the growth rate, but also vitamin content, biomass or color of the plants.
A light recipe can also be about an intensity or spectral modulation over time. The illumination can be adapted to different growth stages of the plants, for instance from germination over growth to fructification. As discussed for instance in “Resizable growth area”, “Hydroponics” or “Horticulture processing line”, different illumination setups can be arranged at different locations or zones of the farm, allowing for light fixtures or arrangements to be customized regarding the specific recipe. However, for sure, different lighting conditions can also be applied with an adjustable light fixture having tuneable light sources with different spectral properties. Independently of the setup in detail, the failure handling of the “Automatic failure compensation” may be of interest, since light recipes rely on working light fixtures. With this intrinsic compensation of a failing light source (e.g. LED), the functionality of the light recipe can be assured.
In an automated farm, the light recipe can be part of a growth recipe comprising or defining further parameters, as for instance the temperature, humidity, CO 2 -level, airspeed EC, pH-value or the like. In “Temperature Dependent Illumination”, the interaction of these parameters is discussed, in particular the interaction between temperature and illumination. In a vertical farm for instance, a different illumination can be applied at different height levels to counteract for example a spread in time to flower, which could result from a higher temperature at the upper shelves due to convection.
In general, one can strive for a perfectly adapted illumination, in particular regarding the spectral composition of the light. According to the “Adaptive Spectrum”, the difference or gap between the ambient light in the farm and an ideal illumination is measured, and the illumination is adapted to “fill up” this gap. The ambient light can for instance be residual daylight, allowing for an overall energy efficient and still customized illumination.
A growth or in particular light recipe can be a fixed data set comprising spectral properties and also information on time intervals and the like. Even though the spectral data is available in this generic form, there can be a missing link to the actual control parameters for operating or controlling a specific light fixture or luminaire. “Spectrum Calculation” is about translating a generic recipe into parameters for a light fixture actually used in the farm. Such a translation may also be relevant for any change of the light recipe.
A change of the recipe may not only depend on a customer request (“Flexible Growth”), the ambient illumination (“Adaptive spectrum”) or a temperature gradient (“Temperature Dependent Illumination”), but might be also used to induce a “Plant Movement”. According to “Plant Movement”, the light intensity is moved above the plants to induce them to follow, comparable to sunflowers following the sun. The movement can strengthen the plants.
For transmitting amended control parameters to a light fixture or its control unit, a wire based or wireless communication is possible. An interesting option is described in “Light Recipes and VLC”, namely a data transfer via a modulation of the light itself. By modulating the emission, for instance, a change in control parameters can be communicated from one light fixture to the other across the farm or respective zone of the farm. On the other hand, “Light Recipes and VLC” considers an adaption of the light recipes to assure that, despite of a reduced intensity resulting from the modulation, for instance the required DLI Level is met.
›INTRODUCTION · 6 of 7
As described in “Extended Recipes”, apart from a spectral adjustment (intensity of certain colors), light recipes can also be implemented by other means to save energy, for instance by optics. Beyond illumination, plant growth can also be modified using a “Temperature control” or by adjusting other parameters, like for instance CO 2 , humidity or the like. Comparable to the light recipes, also the other parameters can be adapted to a specific growth stage of the plants and change over time.
Luminaire
The elements of the disclosure discussed in this chapter “Luminaire” address an agricultural light fixture, particularly horticultural light fixture.
An agricultural light fixture or agricultural luminaire provides illumination for an agricultural arrangement, e.g. a cultivated area or any other target area or target space, in a controlled agricultural system. The illumination may comprise light in the visible range (VIS), the ultraviolet range (UV) and infrared range (IR) of the electromagnetic spectrum. Luminaires can contain a variety of light sources, sensors, actuators and heat dissipation elements, and may be connected to the controlled agricultural system. Furthermore, luminaires can have adaptable features like form change and change of optics.
In an outdoor farm or in a greenhouse, the plants are typically illuminated by the sunlight, wherein artificial lighting can be a supplementation in terms of the spectral composition or amount of light. The latter can be described by the daily light integral (DLI) describing the number of photosynthetically active photons delivered to a specific area over a 24 hour period. On the other hand, indoor farming is also possible without any natural light at all but artificial lighting only.
Traditional luminaires or lighting fixtures are arranged above a target region, which is to be illuminated. Thus, plants grown in or on such target regions commonly will only be illuminated from the top, mainly with vertical light incidence. Consequently, those parts of the plants, which are closest to the light source will receive most of the light. Leaves or bigger plant parts will block light from reaching the lower parts of the plants and therefore sufficient illumination or delivery of light to lower plant parts cannot be guaranteed. In particular, for ranking plants, such as tomatoes, or for fast growing plants, like Cannabis , the upper plant parts will block a significant portion of the light. A homogeneous light distribution over the entire plant therefore might not be achieved.
Further, traditional luminaires often have an illumination profile, which decreases toward the edge and therefore might not illuminate an area homogeneously. In addition, in particular modern luminaires based on semiconductors produce significant heat, which may cause a local heating of the illuminated products in such vertical farms.
LED light-sources used in existing systems may cause irregular illumination, if the distances to the plants are too small, while higher distances may result in light intensities lower as desired, in particular for specific purposes, such as pest or disease control (see also element “Disease & Pest Control” in group “Plant Health & Growth”), or influencing plant growth morphology or the enrichment of enzymes in an illuminated plant, or such.
Therefore, it would be advantageous if the light irradiated by the light sources of a light fixture could be directed or guided or distributed such that the illumination of plants would be improved with respect to the disadvantages described above. The element “Light Guides” of the disclosure describes a light module comprising at least one light guide, which enables improved illumination of plants (see below).
A failing light source, in particular a failing light fixture or light fixture module, can lead to an insufficient illumination of the plants grown in a controlled agricultural system. This does not only relate to the intensity, for instance a reduced DLI (Daily Light Integral), but also to the spectral composition of the light.
Typically, light sources having different spectral properties are provided for achieving light with a defined spectrum optimized for the type of plants grown in the farm, even in terms of their growth stage. Vice versa, one or more failing light sources with a reduced emission or even no emission at all (total failure) can have a negative impact on the health and growth behaviour of the plants.
Thus, it would be advantageous to be able to detect a failing light source quickly so that a repair or replacement action, or any other countermeasure, can be taken promptly. The element “Failure Detection” of the disclosure describes how to detect and locate a failing light source (see below).
Furthermore, it would be advantageous to be able to compensated, at least temporarily, a failing light source until the failed light source, or the affected module, or the light fixture as a whole, is replaced or repaired. The element “Failure Compensation” of the disclosure describes how to compensate a failing light source, at least temporarily (see below).
Agricultural light fixtures used in greenhouses or indoor farms are increasingly LED-based as they can provide a more specific spectrum (light recipe) and use less energy. However, the LEDs nevertheless produce a significant amount of heat, which is usually taken away from the agricultural light fixture using heat spreaders, heat pipes or other solutions to cool the LEDs and prevent an overheating of the LEDs and the surrounding electronics. The thus removed heat-energy is usually lost for further usage.
It has been observed that providing heat to plants from above or sideways can support the growth of the plants and their fruits. Furthermore, if the surrounding temperature moves below the dew point at the plants, there is an increased risk of fungus infection due to higher condensation on the leaves.
Therefore, it would be advantageous to be able to use the waste heat from the LEDs for the plants. The element “Heat Reflector” of the disclosure describes how to direct the waste heat to the plants in a controlled manner (see below).
›INTRODUCTION · 7 of 7
Smart Grid
Agricultural Facilities, for example, horticultural facilities in Controlled Environment Agriculture (CEA), such as greenhouses and vertical farms, need significant amounts of electrical energy. In fact, vertical farms and similar devices (agricultural plants) are major electricity consumers for their illumination and further components (water supply, etc.).
In a conventional grid power supply, the supply of electricity is determined by the consumption by consumers. In a smart grid power supply, the consumption by the consumers can be determined by the supply of the grid power supply since the consumer obtains information about the availability of the electricity (as a rule, by way of the price, which drops when the supply is high) in this case. In particular, there may be a price difference between the energy supply during the day and at night, when less energy is consumed (the day and night rhythm may be inverted).
Therefore, it would be advantageous if an agricultural facility could benefit from low energy price without loss of yield. The element “Smart Grid” of the disclosure describes a controlled agricultural system that is able to make an optimal use of cost-effective electricity.
Customer Interaction
The elements of the disclosure discussed in this chapter “Customer Interaction” address communications and interactions between the controlled agricultural system and customers. For instance, the controlled agricultural system may receive inputs from the customer and provide information to the customer.
These days, customers are only able to order the amount of a plant (biomass). The quality of the plant to be ordered is only determined by quality classes, i.e. size, color, certification marks such as eco- or organic product and fair trade, from which the customer can make a selection. However, it would be advantageous if a more specific definition and/or influence on the quality could be possible when ordering plants, fruit or vegetables. The element “Customer Requirements” of the disclosure describes a controlled agricultural system and a method for customized plant growth.
However, growth recipes, that is, control parameters regarding e.g. illumination, temperature, humidity, nutrients, etc., do not only depend on the specific plant but also on the environment in which the plant is growing. Furthermore, growth recipes for specific customer demands might not be available and need to be extrapolated from existing growth recipes. Therefore, it would be advantageous if a kind of success score for meeting the customer's request were available. The element “Success Score” of the disclosure describes a controlled agricultural system, which is able to provide a probability (success score) to reach the desired goal, namely a customized plant growth.
Growers who grow plants in controlled environments want to constantly monitor, track and optimize plant growth to decrease risk of mold and pest infestation, predict yield and optimize conditions to increase plant quality and yield. These controlled environments can include greenhouses, vertical farms, indoor farms, smart gardening kitchen appliances or instore farms. Climate control systems and ambient sensors collect relevant data like PAR, humidity, CO2, temperature, pH, EC, etc.
Furthermore, growers may want to share pictures and the overall plant growth results on social media platforms like Instagram. Therefore, growers may want to take pictures with their smartphones or any similar mobile device (e.g. tablet PC) or even a camera.
The element “Picture Taking & Evaluation” of the disclosure proposes a method for agricultural management, which targets these needs.
Customers may also prefer produce from eco-farming, i.e. produce that have been grown and delivered with low carbon-food print or without the use of pesticides. The element “Eco Certificates” of the disclosure proposes a method for agricultural management, which considers and tracks ecological aspects with the help of a life-cycle assessment. Furthermore, by means of certificates, customers can verify that the products have been produced eco-friendly.
It is well known that medical plants, which also include cannabis products, play an important role for the health of humans and animals. By way of example, these can contribute to the provision of relief in the case of atopic dermatitis, erythema, pruritus, nervous restlessness, allergies, psoriasis (skin disorder), asthma, intolerance to light, rheumatic ailments, muscle weakness, period pain, epilepsy, tumor and many more.
Medical products can be purchased or ordered in a pharmacy, in relevant specialist stores or already, in part, by mail order as well. However, a customer has no direct influence on the quality of the wares in this case, for example on the light recipe for plant illumination or further growth conditions, and consequently they are also unable to purchase a product that has been adapted or optimized to the personal situation or requirements.
Thus, it would be advantageous if customers could order a medical plant with knowledge of the illumination scenarios the latter experienced during its seedling, growth and maturing stage and with knowledge of what growth conditions were applied.
The element “Medical Certificates” of the disclosure proposes a method for agricultural management, which align to these customer demands by providing products grown under conditions tailored for a specific use, particularly medical use. The intended use and/or content of active agents of the plants may also be certified.
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System Setup
“Resizable Growth Area”
Below, various aspects and details of the “Resizable Growth Area” are discussed.
1 st aspect of the “Resizable Growth Area”: A growth area having a plurality of growth locations, each growth location being provided for growing a plant respectively, wherein a distance between the growth locations is adjustable.
Across the growth area, a plurality of growth locations are provided, for instance carriers like trays or shells or the like. With the growth area adjustable in size, the distance between the growth locations can be adjusted depending on the plant's growth (morphology) or other needs.
The growth area can have a rather small size at the beginning of a growth cycle, for instance after seeding or bedding the plants. Having the plants close to each other can be advantageous in regard to the artificial lighting, as only a comparably small area has to be illuminated. When the plants grow, the distance between the growth locations can be increased, and the illuminated area can be adapted accordingly. In general, this can be an adaption in distance, size, inclination, spectrum, heating, etc. In particular, the inclination of the light fixtures and/or light sources and/or the optics could be beneficial. In addition, the spectrum and intensity could be changed.
Due to the resizable growth area, each plant has sufficient space to allow a proper growth. On the other hand, the plants can be kept close to each other as far as possible, enabling an energy efficient artificial lighting. Assuring small or even no intermediate spaces between the plants prevents a waste of light there.
In contrast, in case of a growth area having a fixed size, the percentage of the area covered by the plants/leaves with respect to the uncovered area would be rather small at the beginning of the growth cycle. The photon energy would be wasted to a large extent, because many photons would just reach the ground without being absorbed by the plants/leaves. On the other hand, placing the plants too close to each other in a predefined distance would negatively impact the growth later on.
2 nd aspect of the “Resizable Growth Area”: The growth area according to the 1 st aspect of the “Resizable Growth Area”, comprising a foil that forms the growth locations, the foil being stretchable to adjust the distance between the growth locations.
The foil can for instance be a plastic or synthetic film or foil. By stretching the foil, the size of the growth area and the distance between the growth locations can be increased. The growth locations can for instance be plant pots or trays attached to the foil, for instance by gluing.
3 rd aspect of the “Resizable Growth Area”: The growth area according to the 1 st or 2 nd aspect of the “Resizable Growth Area”, comprising a plurality of bars that forms the growth locations, interconnected with each other in joints in an articulated manner allowing for folding, in particular lateral folding.
By folding the bars together, the distance between the growth locations can be decreased, unfolding the bars increases the size of the growth area and thus the distance between the growth locations. “Lateral” refers to a direction parallel to the growth area. In a typical application, the growth area can lie horizontally so that the lateral directions are horizontal directions. However, in general, the growth area can also be oriented in the vertical direction, for instance in case of a vertical farm.
In other words, the growth locations are in some embodiments/implementations connected with each other such that they are linked independently of the size of the growth area. In other words, a connecting means (e.g. the foil or bars) holds the growth locations together when different sizes of the growth area are adjusted. Basically, the aforementioned foil can also be combined with the interconnected bars. The latter can for instance provide a mechanical support, the foil can prevent a dirtying of the bars. In some embodiments/implementations, the foil and the bars are alternatives.
4 th aspect of the “Resizable Growth Area”: The growth area according to the 3 rd aspect of the “Resizable Growth Area”, wherein the interconnected bars form a scissors mechanism, the joints being connected operatively with each other.
This means that a position adjustment of one of the joints causes also a position adjustment of one or more other joints. Accordingly, the size of the growth area can be adjusted with a reduced number of actuators, it is not necessary to equip each joint/bar with its own actuator.
5 th aspect of the “Resizable Growth Area”: The growth area according to the 3 rd or 4 th aspect of the “Resizable Growth Area”, wherein the bars form a flexible grid, the bars extending parallelly to each other in groups, the bars of the different groups crossing each other.
Seen in a top view, the bars form a plurality of parallelograms. At the crossing locations, the joints are provided, interconnecting the bars of the different groups with each other. The growth area can be adjusted in size comparable to a vertical or stair-case like scissor lift.
6 th aspect of the “Resizable Growth Area”: The growth area according to the 3 rd or 4 th aspect of the “Resizable Growth Area”, wherein the bars form a flexible Hoberman-type ring which can expand in at least two directions, in particular two directions lying perpendicular to each other.
A Hoberman-sphere is for instance described in U.S. Pat. No. 5,024,031, this sphere is assembled from a plurality of Hoberman-rings. In the present case, the Hoberman-ring is used as the growth area, enabling for instance a more or less rotationally symmetrical size adjustment. Of course, other geometrical shapes are also possible, for example trapezoidal and polygonal structures, foldable structures that form a tessellated area, rotational arrangements with coplanar sides, pivotably linked support brackets, scissor-like extendable structures and the like.
7 th aspect of the “Resizable Growth Area”: The growth area according to the 1 st aspect of the “Resizable Growth Area”, being assembled from a plurality of subareas forming a growth location respectively, wherein the subareas are designed for floating on water like a raft and can be connected and disconnected to adjust the distance between the growth locations.
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At the beginning of a growth cycle, the connected subareas are held together closely, resulting in a growth area of a rather small overall size. As the plants reach the next growth stage, the subareas are disconnected so that the growth area is split up. The subareas will then float independently providing sufficient space for the plants to grow.
The connection/disconnection of the subareas can be achieved by a reversible mechanism, for instance a form-fit or snap-in mechanism. On the other hand, an irreversible mechanism is possible as well, and the disconnection can be achieved by for instance scissors or saws.
In particular, the floating subareas can be designed as carriers penetrable for liquids like water, as described in the element “Aquaponics”, they can float on a waterway described in this element of the disclosure.
The aspects below relate to an Agricultural System comprising a resizable growth area.
8 th aspect of the “Resizable Growth Area”: An Agricultural System, particularly for plant breeding, growing, cultivating and harvesting, comprising:
a growth area according to one of the 1 st to 7 th aspect of the “Resizable Growth Area”, a light fixture for illuminating at least a part of the growth area,
wherein the Agricultural System is configured for adjusting the size of the growth area by adjusting the distance between the growth locations.
In particular, a plurality of light fixtures can be provided, see below. In some embodiments/implementations, the size adjustment is motor-driven, the agricultural system comprising an actuator device with one or more actuators to adjust the size. For instance, the actuators can stretch the foil or move the bars, as described above.
9 th aspect of the “Resizable Growth Area”: The Agricultural System according to the 8 th aspect of the “Resizable Growth Area”, the Agricultural System configured for an adaptive illumination of illumination areas having different sizes.
With the adaption, illumination areas differing in size can be illuminated so that the illumination can be adapted to the size adjustment of the growth area. Illuminating only the area actually occupied by plants is advantageous in terms of energy consumption, see above. The Agricultural System being “configured” means in particular that it can comprise a computing and/or control device programmed accordingly (to trigger an actuator and/or the illumination).
10 th aspect of the “Resizable Growth Area”: The Agricultural System according to the 9 th aspect of the “Resizable Growth Area”, wherein the illumination areas of different sizes are arranged at the same location, wherein only some light sources or light fixtures are switched on for illuminating a small growth area and additional light sources or light fixtures are switched on for illuminating a larger growth area.
In other words, the small area(s) is/are contained in the larger one(s). Therein, only one or some light sources/light fixtures are switched on for illuminating a small growth area and additional light sources/light fixtures are switched on for illuminating larger growth areas.
11 th aspect of the “Resizable Growth Area”: The Agricultural System according to the 10 th aspect of the “Resizable Growth Area”, the Agricultural System configured to shift and/or rotate the growth area and the illumination areas with respect to each other to control an overlap of the growth area and a respective illumination area.
By controlling the overlap, the illumination and/or irradiance of the growth area can for instance be optimized. In a stationary reference system, either the growth area or the illumination setup can be moved for this optimization. In general, optimizing the overlap can support an efficient use of the light sources. For instance in case of elongated luminaires, the size adjustment of the growth area could result in a disadvantageous partial coverage. Adjusting the relative position of the growth area allows, as the case may be, also switching off some light sources or fixtures even though more light sources are used in total (in case of a larger growth area).
Depending on the construction of the growth area, a length elongation of the carrier can lead to a width reduction, for instance in case of a scissor mechanism described above. There, light sources/fixtures that are no longer needed due to the width reduction can be switched off.
In general, the adaptive illumination can be achieved by switching light fixtures on or off as a whole. However, alternatively or in addition, it is also possible to switch individual light sources belonging to the same light fixture. Depending on the illumination area required, for instance one half of the light fixture could be switched on, the other half being added if required.
12 th aspect of the “Resizable Growth Area”: The Agricultural System of the 9 th aspect of the “Resizable Growth Area”, wherein the illumination areas of different sizes are arranged at different locations which are respectively equipped with a respective light fixture, the different sizes of the illumination areas being adapted to different sizes of the growth area, the Agricultural System configured to move the growth area from one illumination area at one location to another illumination area at another location, based on the size of the growth area.
The illumination areas differing in size are not arranged at the same location, instead the growth area is moved to another part of the farm. In addition to the relocation, the growth area can be rotated to control an overlap. The different illumination areas can be arranged side by side, but they can also be provided in different rooms of the farm. For the transportation, a conveyer belt or roller mechanism can be used for instance. Further, also a waterway can be used for transporting the growth area, in particular in case of the connected/disconnectable subareas.
13 th aspect of the “Resizable Growth Area”: The Agricultural System according to any one of the 8 th to 12 th aspect of the “Resizable Growth Area”, comprising an actuator device with one or more actuators able to adjust the size of the growth area, namely the distance between the growth locations.
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14 th aspect of the “Resizable Growth Area”: The Agricultural System according to the 13 th aspect of the “Resizable Growth Area”, comprising a sensor device for sensing growth data of the plants and a computing device configured to processing the growth data measured by the sensor device and to initiate the actuator device to adjust the distance between the growth locations based on the growth data, namely to vary the distance between the growth locations and hence the size of the growth area as the plants grow.
The data measured by the sensor device can be processed by a computing device, which initiates the actuator device to adjust the size of the growth area as required. The distance between the growth location can for instance be increased as the plants grow.
15 th aspect of the “Resizable Growth Area”: The Agricultural System according to the 14 th aspect of the “Resizable Growth Area”, wherein the sensor device comprises an image capture device and the processing by the computing device comprises image recognition.
The image capture device can for example be a camera, it can be used to determine the actual size of the plants. The images taken can be processed by a picture recognition. In a simple approach, for instance, the number of independent plants can be counted, and the size of the growth area can be increased if two plants become so close that they appear as one.
16 th aspect of the “Resizable Growth Area”: An Agricultural System, comprising:
a growth area having a plurality of growth locations for growing plants, a sensor device for sensing growth data of the plants, an actuator device, and a computing device, wherein the actuator device is configured for adjusting a distance between the growth locations and hence a size of the growth area, and wherein the computing device is configured to process the growth data measured by the sensor device and initiate the actuator device to adjust the size of the growth area based on the growth data, namely to vary the distance between the growth locations and hence the size of the growth area as the plants grow.
17 th aspect of the “Resizable Growth Area”: The Agricultural System of the 16 th aspect of “Resizable Growth Area”, comprising
a plurality of bars that forms the growth locations of the growth area, a plurality of light fixtures for illuminating illumination areas, and an image capture device comprised in the sensor device, wherein the bars form a flexible grid, interconnected with each other in joints in an articulated manner allowing for folding, the joints being operatively connected with each other forming a scissors mechanism, wherein, in the flexible grid, the bars extend parallel to each other in groups, the bars of the different groups crossing each other, wherein the illumination areas have different sizes and are arranged at different locations the different sizes of the illumination areas being adapted to different sizes of the growth area, the Agricultural System configured to move the growth area from one illumination area at one location to another illumination area at another location, based on the size of the growth area, and wherein the growth data, based on which the size of the growth area is adjusted, comprises images, the processing by the computing device comprising an image recognition.
18 th aspect of the “Resizable Growth Area”: A Method for using a growth area according to any one of the 1 st to 7 th aspect of the “Resizable Growth Area”, or an Agricultural System according to any one of the 8 th to 17 th aspect of the “Resizable Growth Area”, comprising the steps:
growing plants at the growth locations, adjusting the distance between the growth locations based on the growth of the plants.
In some embodiments/implementations, this adjustment is done or triggered automatically by a computing device connected with a sensor device for sensing the growth and an actuator device, triggered by the computing device (e.g. via a control unit), for adjusting the size of the growth area.
19 th aspect of the “Resizable Growth Area”: A Method for agriculture, comprising at least one Agricultural System, and comprising:
growing plants.
20 th aspect of the “Resizable Growth Area”: A Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of an Agricultural System, cause the Agricultural System to apply defined growing conditions to the plants.
The application of “defined growing conditions” may for instance be: applying a light recipe, adjusting a temperature, and/or adjusting a CO 2 content. The defined growing conditions can for instance be comprised in growth recipe, see below for illustration.
21 th aspect of the “Resizable Growth Area”: Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of an Agricultural System according to any one of the 8 th to 17 th aspect of the “Resizable Growth Area”, cause the Agricultural System to execute an adjustment of the distance between the growth locations.
Regarding further details, reference is made to the description above. The program instructions can be pre-programmed or calculated based on measurement values. Pre-programmed instructions can for instance follow linear or non-linear function over time (or over total Photon Flux or any other photometric value, or assumed plant leaf density index), or first exponential, then logarithmic etc.
“Hydroponics”
This element of the disclosure relates in particular to floating grow fields and a respective waterway for moving them through the farm.
1 st aspect of “Hydroponics”: A Grow field for a hydroponic arrangement, comprising a carrier for carrying plants, wherein the carrier is designed to be penetrable for liquids like water.
This element of the disclosure solves the problem of how to provide irrigation and nutrients to the plants and yet allows for transportation of the plants through the farm over the growth cycle. It is proposed that the plants grow in small grow fields filled with materials as used in hydroponics, e.g. expanded clay aggregates, growstones, perlite, pumice, rock wool etc. The grow fields are surrounded by water. Each grow field may contain a single plant or several plants. The roots of the plants may be hanging in the water. The water is used to provide irrigation and nutrients. However, the small grow fields are not fixed and surrounded by flowing water, but movable within the surrounding water.
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2 nd aspect of “Hydroponics”: The Grow field according to the 1 st aspect of “Hydroponics”, wherein the carrier is designed for floating on water like a raft.
The preferred design is thus not the form of a plant pot, but a form that resembles a raft and allows floating on the water without tilting over. The sides of the small grow fields, especially the backside lying in the water, comprise a grid-like structure, so they hold back the plants and the grow materials but let in the water.
Seen in a top view, the shape of the grow fields can be quadratic, rectangular, hexagonal, circular, or freeform. Grow fields for the same kind of plant can have the same form. Grow fields for another kind of plant can have a different form. In this way, different shapes may facilitate identification of various kinds of plants. Furthermore, the shape can influence the drift velocity. Grow fields may be connected with each other (e.g. by magnets or any other connecting means like for instance form-fit members, see also the 7 th aspect of “Resizable Growth Area”), so that they form a chain of grow fields and float collectively.
The grow fields may be equipped with a variety of sensors and e.g. RFID or WLAN chips that transpond/repeat/send information to a reading device for asset tracking. Such reading devices may be arranged in light fixtures that may be arranged above the grow fields for irradiating/illuminating the plants.
3 rd aspect of “Hydroponics”: The Grow field according to the 1 st aspect of “Hydroponics”, wherein wheels are connected to the carrier for rolling on the bottom of an area covered with water, while keeping the carrier like floating on the water surface.
In this case, the rafts floating on the water could be replaced by trays with wheels, which are rolling on the bottom of the water tank. In this case, the movement of the grow fields/plants can be assured by the inclination of the water tank alone.
4 th aspect of “Hydroponics”: A Hydroponic arrangement, comprising one or more grow fields according to any one of the preceding aspects of “Hydroponics”, and further comprising a waterway, wherein the grow fields are movably arranged on the surface of the waterway.
The waterway, in which the small grow fields are floating, may be an elongated water tank, which is open on its upper side, i.e. the water surface. The small grow fields are floating on the water surface from one side of the water tank (start) to the other (end), along its long side. In some embodiments/implementations, the time it takes a grow field to reach the end coincides with the time it takes for the respective plant to be ready for harvesting. A distance between start and end can for instance be at least 2 m, 4 m, 6 m or 8 m (with possible upper limits of for instance not more than 500 m, 200 m or 100 m).
5 th aspect of “Hydroponics”: The Hydroponic arrangement according to the 4 th aspect of “Hydroponics”, configured to establish a water flow on the surface of the waterway.
The water flow can move the grow fields along the waterway.
6 th aspect of “Hydroponics”: The Hydroponic arrangement according to the 4 th or 5 th aspect of “Hydroponics”, further comprising one or more inlets arranged at the waterway for the inflow of water.
In particular, the inflowing water can generate the water flow for moving the grow fields.
7 th aspect of “Hydroponics”: The Hydroponic arrangement according to the 5 th or 6 th aspect of “Hydroponics”, wherein the grow fields are able to float on the surface of the waterway along the water flow.
To summarize, the floating of the plants from the first end (start) to the final end (where they can be harvested) can be assured e.g. by:
An inclination of the ground of the water tank, which provides the waterway (or an inclination of the whole water tank) towards the final end, where the waterway contains a sink for the water, so that the water automatically flows towards the final end and/or, Water inlets or nozzles attached at the first end and/or at the side of the water tank (in some embodiments/implementations arranged close to the water surface) pointing towards the final end and thus inducing a direction of flow on the water.
The water inlets do not only provide fresh water, they also provide the nutrients needed for the plants (like phosphor, oxygen dissolved in the water, . . . ). Therefore, in some embodiments/implementations, the water inlets are attached to the side of the water tank in any case, although they do not necessarily have to point to the final end of the water tank if the water flow is assured by the inclination of the tank.
In a preferred embodiment, the water tank also contains at least one sink to remove the water from the water tank as the water inlets add water. In this way, a flow on the surface of the water may be established without raising the level of the water in the water tank.
8 th aspect of “Hydroponics”: The Hydroponic arrangement according to any one of the 4 th to 7 th aspect of “Hydroponics”, further comprising one or more light fixtures arranged above the surface of the waterway.
The floating speed of the small grow fields can be controlled by the inclination of the water tank and/or the speed with which the water inlets blow the water into the tank. However, it may be advantageous, e.g. in a small tank (i.e. where the small grow fields would only need to move very slowly to reach the final end) to add grids across the tank, which can hold back the small grow fields.
9 th aspect of “Hydroponics”: The Hydroponic arrangement according to any one of the 4 th to 7 th aspect of “Hydroponics”, further comprising one or more grids arranged across the waterway, wherein the grids are able to hold back the grow fields.
With the grids, the water tank can be separated into several grow areas or zones. In each grow area (which is a growth sector or zone), the growth parameters may be different, e.g. nutrients may be added in another concentration or the light intensity or the light spectrum of the light sources of the light fixtures might be different for each grow area. If the plants have reached the end of the growth cycle, the grid is moved aside (to a side, up or down, or open like a water lock) and the grow fields move on to the next growth area where they can be exposed to one or several different grow parameters like illumination, temperature or nutrients. Furthermore, the light intensity and/or light spectrum may also be adjusted to the water flow speed. The waterway at each station/grow area may have a different depth level and temperature than the previous or subsequent one.
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Below, an Agricultural System with a waterway (Hydroponic arrangement) is discussed.
10 th aspect of “Hydroponics”: A Controlled Agricultural System, particularly for hydroponic growth, comprising at least one hydroponic arrangement according to any one of the 4 th to 8 th aspect of “Hydroponics”, further comprising:
an actuator device, comprising one or more actuators able to adjust parameters of the hydroponic arrangement, e.g., water inlet, water sink, water grid, nutrient dosing feeder, light fixture. a data storage device for storing reference data of the parameters of the hydroponic arrangement, a computing device, configured to control the parameters of the hydroponic arrangement by means of the actuator device and based on the data of the parameters stored on the data storage device.
The computing device can control the water flow, and the grow parameters like nutrient concentration and illumination by means of respective actuators. The system may control these parameters based on fixed values provided in a database or based on sensor inputs e.g. from cameras, light sensors, temperature sensors or chemical sensors. The database is stored in a data storage device that may be based locally, in a network or the cloud.
11 th aspect of “Hydroponics”: The Controlled Agricultural System according to the 10 th aspect of “Hydroponics”, further comprising a sensor device.
The sensor device can comprise one or more sensors able to sense/detect growth parameters of the plants on the grow fields and/or control parameters of the hydroponic arrangement, e.g. flow speed indicator, thermometer, photometer, color detector, camera.
12 th aspect of “Hydroponics”: The Controlled Agricultural System according to the 10 th or 11 th aspect of “Hydroponics”, further comprising a user interface configured to deliver the growth status of the plants on the grow fields and/or the status of the hydroponic arrangement.
The information about the growth status or the status of the grow system can be provided to customers, the farmer or other third parties.
13 th aspect of “Hydroponics”: A Method for agricultural management, particularly for hydroponic growth, comprising:
at least one controlled agricultural system according to any of the 10 th to 12 th aspect of “Hydroponics”, and the steps of planting one or more plants into one or more grow fields, putting the grow fields at a first position on the water surface of the waterway of the hydroponic arrangement, adjusting the parameters of the hydroponic arrangement, e.g. water flow, illumination, controlling of the grids, concentration of nutrients in the water of the waterway, temperature of water and/or ambient air, by means of the actuator device and based on respective data of the parameters retrieved from the data storage device, with the goal that the plants are ready for harvest when they arrive downstream at a final position, moving the grow fields on the water surface from the first position of the waterway downstream to the final position of the waterway, removing the grow fields from the water surface at the final position of the waterway.
14 th aspect of “Hydroponics”: A Method for agricultural management according to the 13 th aspect of “Hydroponics”, further comprising the step of
Sensing growth parameters of the plants by means of the sensor device, and
readjusting the parameters of the hydroponic arrangement according to the sensed growth parameter.
15 th aspect of “Hydroponics”: A Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 10 th to 12 th aspect of “Hydroponics”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 13 th to 14 th aspect of “Hydroponics”.
“Horticulture Processing Line”
This element of the disclosure describes an automated processing line for growing plants.
1 st aspect of the “Horticulture Processing Line”: A Controlled Agricultural System comprising
a processing line having different growth zones where defined growth conditions can be applied, growth trays for respectively growing at least one plant, the growth trays being moveable along the processing line from a first growth zone to a last growth zone, a treatment location where defined treatment conditions can be applied, wherein the Controlled Agricultural System is configured for moving the growth trays along the processing line, wherein at least one tray, but not all trays, is unloaded from the processing line to the treatment location prior to having reached the last growth zone.
In each growth zone, defined growth conditions can be applied, for instance a defined illumination (intensity/spectral composition), temperature, humidity or the like. At each growth zone, the growth conditions can be optimized regarding a certain growth stage of the plants. In case of a Hydroponic arrangement (see “Hydroponics”), the growth zone can be a “grow area” discussed there (see in particular the 9 th aspect of “Hydroponics”).
In general, the first growth zone can for instance be optimized for the sawing or seeding or for an early growth stage. After having reached a certain size or growth stage, the plants may require other growth conditions to maximize the yield. Humidity and temperature may for instance be lower than during early seeding. Accordingly, the plants can be moved to the next growth zone of the processing line. After a further growth there, the plants are moved to the next growth zone until they reach their final growth stage, becoming ready for harvesting in the last growth zone.
For moving the plants along the processing line, the agricultural system is equipped with growth trays (e.g. grow fields in “Hydroponics”). Depending on the size, the trays can receive a container or receptible or the like, they can also have a bowl- or receptible-like shape themselves. In general words, a defined volume for receiving soil or hydroponics or any other matrix material for growing plants is provided at each growth tray. Depending on the type of plants grown, at least one or also a plurality of plants can be grown at or on each growth tray.
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The agricultural system is configured for moving the growth trays along the processing line, either continuously (like in a conveyer oven) or in steps from sector to sector. In the latter case, the growth trays are moved on further after having stayed a certain time at the respective growth zone, which can be predefined or depend from growth data measured with a sensor device, for instance a camera or the like. Regarding a possible design of growth trays and/or a setup for moving them, reference is again made to “Hydroponics”. Further, the growth trays can also be connected in groups, each group forming or being a resizable growth area. Those growth areas can be moved through the farm as described in “Resizable Growth Area”.
According to the element “Horticulture Processing Line”, the agricultural system additionally comprises a treatment location. There, defined treatment conditions can be applied, see in detail below. Therein, the agricultural system is configured to unloading one or some of the trays from the processing line prior to having reached the last growth zone, while other trays pass by on the processing line. In some embodiments/implementations, this is done automatically. The other trays are moved further from sector to sector along the processing line.
2 nd aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of the 1 st aspect of the “Horticulture Processing Line”, configured for reloading the at least one tray to the processing line after the treatment at the treatment location.
Thus, the at least one tray is reloaded to the processing line later on. In a simple setup, it might be reloaded via the first growth zone, even though the growth conditions there might not be appropriate for plants having been unloaded at a later stage.
3 rd aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of the 2 nd aspect of the “Horticulture Processing Line”, configured for reloading the at least one tray to the processing line at that growth zone where it has been unloaded.
In case of a preferred system with a clocked operation (trays moved from sector to sector after a respective time interval), a gap can be left between two trays fed one after the other to the first growth zone. Due to the clocked movement, the gap propagates along the processing line, until the tray of the treatment location is reloaded into the gap at the appropriate processing stage.
4 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects of “Horticulture Processing Line”, wherein the trays are moved along the processing line from one growth zone to another pursuant to a predefined clocking.
5 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of the 3 rd and 4 th aspect of the “Horticulture Processing Line”, configured for leaving a gap between two trays fed one after the other to the first growth zone, wherein the at least one tray is reloaded to the processing line into the gap.
Providing a treatment location for selectively unloading trays from the processing line can enable a high output and good quality, while only a minor or even no human interaction or support is required. Since only a few trays are unloaded selectively, the overall throughput remains high. For instance, not more than 40%, 30%, 20% or 15% of the trays can be unloaded to the treatment location (with possible lower limits of for example 1%, 2% or 3%). Unloading individual trays from the processing line can also protect the trays remaining on the processing line, for instance in case of a pest or fungal infestation or other contamination. Further criteria for unloading plants from the processing line can be their size (too small/too large) or fruit yield (too few/too many fruits).
6 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, configured for unloading the at least one tray based on at least one of
a plant size, a plant morphology, a fruit yield, a biological or chemical fruit ripeness indicator, a pest infestation, a fungal infestation, a contamination.
As described above, the growth conditions at each growth zone may be optimized regarding the respective growth stage. The unloading of individual trays can also be used for a further optimization of the growth conditions applied at a specific sector. For instance, the light recipe, e.g. the spectral composition or intensity of the light, can be adapted, not only to the plant type, but even to individual lots.
7 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein the treatment applied at the treatment location is at least one of
an illumination treatment, a low or high temperature treatment, a gas absorption treatment, an insect attraction treatment, a controlled humidity treatment, an UV-radiation treatment, a non-lighting treatment.
To summarize, the treatment applied in the treatment location can be an illumination treatment (specific lighting with VIS, UV and/or IR light), a low or a high temperature treatment, a gas absorption (for instance of ethylene), an insect attraction treatment (to treat a pest infestation) and/or a humidity treatment and/or a non-lighting treatment (OFF-period) in a dark environment. Basically, a manual treatment of an operating personnel is possible, even though a fully automated treatment is preferred.
A target of the treatment applied may be to reduce or eliminate any deviation having been the reason for unloading the tray from the processing line. Alternatively or in addition, a specific measurement may be performed in the treatment location, see above. The tray unloaded from the processing line to the treatment location can be used for optimizing not only the light recipe but also other control parameters like temperature, humidity or the like. In case that the treatment conditions applied at the treatment location have a positive effect on the plant growth, they can be transferred to one or more growth zones of the processing line.
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To protect the plants remaining on the processing line, the treatment location can be a quarantine area. In a worst-case scenario, the plants unloaded could be destroyed to prevent an infestation/contamination of the plants remaining on the processing line.
8 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein the treatment location is a quarantine area.
In general, the tray or trays unloaded from the processing line might be predefined (e.g. every 10th tray) or chosen in a stochastic procedure. The unloading from the processing line to the treatment location could be kind of a lot control, allowing a detailed inspection/monitoring of the plants. In some embodiments/implementations, the unloading is triggered by a sensor measurement.
9 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, comprising a sensor device for sensing plant growth, harvesting time, plant morphology and/or plant health and ripeness, the Controlled Agricultural System being configured for unloading the at least one tray based on a measurement by the sensor device.
In some embodiments/implementations, the agricultural system comprises a plurality of sensor systems, which can be cameras, distance measuring devices or the like. A sensor device can for instance be integrated into a light fixture comprising the light sources for the lighting. Alternatively or in addition, a sensor device can be integrated into the tray. A sensor device at the tray can monitor the conditions that have been applied to the plants so far (e.g. temperature, illumination and so on).
10 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, configured for storing growth data, namely data about the growth conditions applied to the growth trays and/or sensor data about plant growth, harvesting time, plant morphology and/or plant health, in a data storage device.
The data storage device can be an internal part of the agricultural system, connected or integrated into the computing device. However, the data storage device can also be provided externally, for instance in the cloud. Data storage and handling can be done using for example a distributed Blockchain ledger system that ensures accuracy and data permanency for each tray and/or sub-tray and/or plant thus allowing a producer or customer to track the history of a specific plant product.
11 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of the 10 th aspect of the “Horticulture Processing Line”, configured for storing the growth data individually for the trays, namely assigned to a respective tray.
The growth data can be data about growth conditions or sensor data measured, is stored individually for the trays. Accordingly, for some or all of the trays, the growth conditions which have been applied/measured for the specific tray are assigned to the tray. In some embodiments/implementations, the trays can be provided with a respective identifier, for instance a barcode, RFID-tag or the like. An identifier can simplify the correlation between the growth data and a specific tray.
12 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein the growth trays are provided with a respective identifier allowing an individualization of the trays.
13 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein a transfer gate for unloading growth trays from the processing line is provided at each growth zone.
In some embodiments/implementations, a plurality of treatment locations are provided along the processing line so that the trays can be unloaded at different growth zones (in different growth stages) to a different treatment location respectively. Therein, in a basic setup, each of the treatment locations can be linked to the processing line solely. Likewise, the trays can be unloaded from and reloaded to the processing line, or be destroyed at the treatment location, but not transferred from one treatment location to the other directly.
14 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein a plurality of treatment locations are provided, linked with each other by a second processing line.
Thus, the trays unloaded from the first processing line can also be moved along the second processing line from one treatment location to another. They can be processed on the second processing line until a final growth stage has been reached or can be reloaded to the first processing line before. Alternatively, the treatment location can be a “blind end” to which the plants are unloaded for treatment or destruction.
15 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein at least a section of the processing line extends horizontally, the growth trays being transported horizontally by vehicles or on a conveyer belt from one growth location to the other.
Horizontally, the growth trays can be transported by vehicles, in particular vehicles driving autonomously. Alternatively or in addition, a conveyer belt can be used for a horizontal transportation. Further, the growth trays could also float along a waterway, see for instance “Hydroponics”. A vertical transportation can be achieved by an elevator, in particular of a paternoster-type elevator.
16 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein at least a section of the processing line extends vertically, the growth trays being transported vertically by an elevator.
17 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of the 16 th aspect of the “Horticulture Processing Line”, wherein the elevator is of a paternoster type.
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18 th aspect of the “Horticulture Processing Line”: The Controlled Agricultural System of one of the preceding aspects, wherein the growth zones are respectively equipped with a light fixture for agricultural lighting.
Each growth zone can be equipped with a plurality of light fixtures, wherein each light fixture can comprise a plurality of light sources, like halogen lamps, discharge lamps, semiconductor LEDs, OLEDs and Laser, and the like. In particular, light sources having different spectral properties can be mixed to adjust a spectral composition which is optimized regarding the specific plants or the growth status. The light fixtures can be installed having a fixed distance to a processing line, for example, a conveyor belt, though the light fixtures in different sectors can have different distances. In another embodiment, the light fixtures can be installed in a flexible way, so that their distance to the plants can be varied over time, in some embodiments/implementations automatically.
19 th aspect of the “Horticulture Processing Line”: A Method for Controlling a Controlled Agricultural System according to one of the preceding aspects,
wherein plants are grown in the growth trays and the growth trays are moved along the processing line, wherein at least one tray is automatically unloaded from the processing line to the treatment location prior to having reached the last growth zone.
20 th aspect of the “Horticulture Processing Line”: A Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 18 th aspect of the “Horticulture Processing Line”, cause the Controlled Agricultural System to execute the Method for Controlling a Controlled Agricultural System according to the 19 th aspect of the “Horticulture Processing Line”.
The program instructions can use the data to calculate/generate a ‘virtual twin facility’, see also “Measuring Patterns” below, of such a controlled agricultural system and show it graphically to a producer or customer for an informed interaction and control.
“Measuring Patterns”
Growers have different demands regarding the plant growth. Furthermore, they want to monitor the plant growth continuously. Demands may comprise plant quantity, plant quality, post-harvesting quality, and/or storage and delivery time. Plant quality is mainly defined by primary and secondary metabolites as well as appearance (color, morphology). Plant quantity is defined by yield (fresh or dry weight). Plants comprise herbs, vine crops, microgreens, leafy greens, fruits and the like.
A growth recipe comprises values for a light recipe (spectrum, intensity, photoperiod), content of CO 2 — and other gases in the air, temperature (air, soil), humidity, nutrients, EC (electrical conductivity), pH, H 2 O, chemical and biological composition of the soil, Hydroponics and aeroponics parameters, etc. A light recipe may comprise a time-sequential set of individual light recipes. However, the actual setup of the agricultural facility/plant growing facility (light sources, light fixtures, placement of light fixtures, actuators, sensors) will be different for almost every grower so that a pre-defined growth recipe might not provide the optimal result. New requirements that have not been tested before might also not lead to the desired results. A recipe may be suited and applicable to generate desired growth conditions in a 2D and 3D agricultural environment.
This is one example, why a group of sensors or a sensor device system, which comprises a plurality of sensors, for measuring the actual plant-growth relevant data can be of interest. This data can for instance be used for triggering actuators and/or can be stored, for example in a general platform, e.g. a digital platform like an online-platform (e.g. in the cloud) or a local data storage device.
1 st aspect of “Measuring Patterns”: A Method for arranging a plurality of sensors in an agricultural facility, e.g. in a plant growing facility,
the sensors being of the same type (first type), wherein i) the sensors are placed in a first relative arrangement in the agricultural facility; ii) a measurement is performed with the sensors being in the first relative arrangement; iii) at least some of the sensors are removed and/or re-positioned.
“Re-positioning” means that the sensors are placed at another location in the agricultural facility and/or are oriented in another direction. Thus, the sensors are re-located and/or re-oriented. For instance in case of optical sensors, e.g. cameras, the re-orientation can change the detection field even without a re-location.
From steps i)/ii) to step iii), the distribution of the sensors can be optimized. This means that the farm is covered sufficiently while the overall number of sensors is kept as low as possible. This can reduce the overall cost of the facility. With the approach described here, an optimum coverage can be achieved nevertheless. In simple words, the agricultural facility is measured with a high (global or local) sensor density initially (first relative arrangement, steps i/ii). In the final setup (step iii), sensors are for instance placed only where the measured values differed significantly (in time or locally). In other words, sensors which do not provide new information, as the data that they are providing is almost identical to neighboring sensors, will be removed/re-positioned. Likewise, the overall number of sensors can be reduced.
The measurement of step ii can for instance cover a time interval of at least 1 hour, 2 hours, 4 hours, or 6 hours. Possible upper limits are for instance 8, 6, 4, or 2 weeks, further possible upper limits being for instance 10 days, 8 days, 6 days or 4 days. Advantageously, a time interval covering one or more days can give an impression over the circadian rhythm of the plants (covering day/night cycles).
The sensors being “of the same type” are adapted for measuring the same physical quantity. In some embodiments/implementations, these sensors are identical in construction. A physical quantity measured can for instance be the temperature, humidity, leaf temperature, VPD (vapor pressure deficit), substrate moisture, substrate temperature, or EC (electrical conductivity), further, the pH-value, wind/air velocity, or PAR (photosynthetically active radiating) can be measured. It is also possible to measure vibrations, or sound, but also camera imaging solutions (including hyperspectral imaging) can be implemented. The sensor system may also be configured to measure the geometrical layout and texture of an agricultural environment, like a vertical farm or a greenhouse.
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The “plurality” of sensors can for instance be at least 5, 10, 20, 30 or 40 sensors (with possible upper limits of for instance not more than 1000, 500 or 100).
2 nd aspect of “Measuring Patterns”: The Method of the 1 st aspect of “Measuring Patterns”, wherein, in the first relative arrangement, a local areal density of the sensors is higher than after step iii).
The local areal density is taken locally, namely in a subarea of the growth area of the farm. The growth area is the total area used for growing plants in the farm. A subarea, in which the local aerial density is taken, can for instance cover not more than 70%, 50% or 30% of the growth area (possible lower limits are for instance at least 1%, 5% or 10%).
3 rd aspect of “Measuring Patterns”: The Method of the 2 nd aspect of “Measuring Patterns”, wherein the sensors are placed in a second relative arrangement prior to step iii), the local areal density of the sensors being higher in the second relative arrangement than after step iii).
The first and the second relative arrangement differ at least partly. From the first to the second relative arrangement, at least some of the sensors are re-positioned.
4 th aspect of “Measuring Patterns”: The Method of the 3 rd aspect of “Measuring Patterns”, wherein all sensors are re-positioned from the first to the second relative arrangement.
Likewise, prior to step iii, the growth area of the farm can be scanned successively. In each relative arrangement, the sensors form a scan field with a high local areal density of the sensors, these scan fields cover the growth area step by step. In a sense, the scan fields are moved across the farm.
5 th aspect of “Measuring Patterns”: The Method of the 3 rd or 4 th aspect of “Measuring Patterns”, wherein the local areal density of the sensors is the same in the first and the second relative arrangement.
6 th aspect of “Measuring Patterns”: The Method of any of the 3 rd to 5 th aspect of “Measuring Patterns”, wherein a first measuring area covered by the sensors in the first relative arrangement and a second measuring area covered by the sensors in the second relative arrangement overlap at most partly, if at all.
The measuring areas are respectively smaller than the overall growth area of the farm (the area of the farm used for growing plants).
7 th aspect of “Measuring Patterns”: The Method of any of the 3 rd to 6 th aspect of “Measuring Patterns”, wherein the number of sensors after step iii) is the same as in step i). Thus, no sensors are removed in step iii).
During the initialization/setup phase, the sensors are moved across the growth area in the high density arrangements (scan fields), thereafter the same sensors are placed with a smaller local aereal to monitor the farm during normal operation.
8 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, wherein, after step iii), a local areal density of the sensors is varying across the farm, the local areal density being
smaller in a subarea, where a smaller deviation between the sensors was observed prior to step iii); and larger in a subarea, where a larger deviation between the sensors was observed prior to step iii).
Therein, “smaller”/“larger” relates to a comparison between the different subareas of the farm.
9 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, wherein a plurality of additional sensors, which are of a second type (different from the first type), are provided, wherein
iv) the additional sensors are placed in a first relative arrangement in the agricultural facility; v) a measurement is performed with the additional sensors being in the first relative arrangement; vi) at least some of the additional sensors are removed or re-positioned.
Therein, the measurements with the first sensors and the additional sensors can be performed one after the other or simultaneously. In other words, steps ii) and v) can be performed at the same time or subsequently.
10 th aspect of “Measuring Patterns”: The Method of the 9 th aspect of “Measuring Patterns”, wherein, after step iii),
a local areal density of the first sensors is smaller in a region where a local areal density of the additional sensors is larger; and/or a local areal density of the additional sensors is smaller in a region where a local areal density of the first sensors is larger.
Likewise, correlations or dependencies between the different sensor types are taken into account to reduce the overall number of sensors. A correlation can for instance exist between temperature and humidity.
10 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, wherein a digital model of the plant growing facility, namely a digital facility twin, is rendered to indicate/suggest the positions of the sensors in the digital model.
In particular, a computing device can be configured to render the digital facility twin. The rendering can be performed based on the data stored in the data storage device. In the digital facility twin, the positions of the sensors for the first relative arrangement (of the first and/or additional sensors) can be indicated/suggested, but also the sensor positions for step iii) and/or step vi).
“Measuring Patterns” can also be implemented into an Agricultural System, configured for performing a method according to any of the preceding aspects of “Measuring Patterns”.
The Agricultural System can be configured to be able to manage the positioning (including orientation and inclination) and re-positioning of the sensors of the sensor devices for monitoring the plant growth and, optionally, the status of the plant growing facility (e.g. for the maintenance of the equipment used in the plant growing facility) based on the data stored in the data storage device. In particular, this element of the disclosure can relate to a Controlled Agricultural System, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, e.g. in a plant growing facility, comprising at least one sensor device, comprising a group of sensors able to measure environmental parameters (e.g. temperature, light intensity, etc.).
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In particular, the Agricultural System can comprise a computing device, configured to be able to access and control the at least one sensor device and the data storage device. In some embodiments/implementations, the computing device is configured for the positioning and re-positioning of the sensor.
The Agricultural System can also comprise a data storage device (e.g. platform/cloud) for storing data about the plant growing facility (e.g. layout, size, placement of light fixtures, actuators, etc.) and the at least one sensor device (e.g. types of sensors in the groups, number of sensors per group, range of sensors, etc.), The positioning and/or re-positioning can be managed based on the data stored in the cloud.
In particular, the computing device can be configured to access and control the sensor device system and the data storage device/platform. Furthermore, the computing device is configured to access the set of measurement data, to analyze them and to compare them with other data sets, for example, stemming from other controlled agricultural systems, or from standardized or ideal data sets or current or historical user data sets.
The sensor device system may comprise a variety of different sensor types in order to measure a variety of relevant plant growth data as well as post-harvest plant data, like the concentration of certain enzymes or the concentration of vitamins and glucose. The sensor device system may comprise a variety of different sensor types in order to measure and recognize pest-related and/or disease related parameters. The sensor device may be configured to establish a communication and/or data processing and analyzing network between themselves.
To create and update the growth recipes, the status of the plant growth and of the plant growth facility needs to be understood. To record the status, a set of sensors need to be deployed in the facility. These sensors may include ambient sensors.
The group of sensors can be able to measure one or more of the following parameters: temperature, humidity, leaf temperature, VPD (vapor pressure deficit), substrate moisture, substrate temperature, EC (electrical conductivity) and pH-value, velocity, PAR (photosynthetically active radiating). Alternatively or in addition, sensors measuring vibrations, sound but also camera imaging solutions including hyperspectral imaging may be used. The sensor system may also be configured to measure the geometrical layout and texture of an agricultural environment, like a vertical farm or a greenhouse. A sensor can also be an optical detection device, particularly for imaging methods, e.g. a camera.
In an aspect of “Measuring Patterns”, the sensors are able to communicate with each other or with a control unit. The sensors may form local sub-systems with a respective control unit. The local sub-systems can be adaptively reconfigured based on output data from an artificial intelligence network system. An overall control unit (e.g. the computing device) may manage data fusion of different sensors and subsequent data analysis as well as data forecasting. The sensor data may be fed into an Artificial Intelligence system that, after calculating, outputs data that can be used for plant modelling and the steering of actuators.
It can be advantageous to find the optimal place for the different sensors to optimize the use of sensors (minimum number needed) and nevertheless get a comprehensive overview about the growth situation.
Therefore, the computing device, is configured to manage the positioning and re-positioning of sensors for monitoring plant growth, plant harvesting, plant placement on empty places and, optionally, the status of the plant growth facility (e.g. for the maintenance of the equipment used in the plant growth facility).
The Controlled Agricultural System can comprise an actuator device able to adjust growth parameters of plants (e.g. water, nutrient, light (intensity, spectrum), humidity, temperature, air ventilation, water circulation, pesticides) and/or to adjust the position and shape of a light fixture and/or to change the layout of variable building design parameters of a building or housing or cabinet of the agricultural facility and/or to close or open the roof of the agricultural facility (e.g. greenhouse) and/or to change a location of a moveable agricultural growth cabinet inside the agricultural facility.
11 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, e.g. a plant growing facility, comprising a controlled agricultural system,
the method comprising the steps of
Uploading/Entering the layout of the plant growth facility into a data storage device of the controlled agricultural system;
Uploading/Entering data of the sensors into the data storage device;
Rendering a digital model of the plant growing facility (digital facility twin) including indicating the positions of the sensors by means of the computing device based on the data stored in the data storage device;
Positioning the sensors in the real plant growing facility according to the model.
First (initial setup), a layout of the plant growth facility is uploaded to the platform (data storage device) incl. all relevant dimensions of the facility and growing zones (length, height, height of traces, distance between rows, amount of rows, etc.). Additionally, the available amount of sensor types and amount of different sensors is entered into the controlled agricultural system, e.g. via a user dashboard. The computing device of the controlled agricultural system is configured to generate a 3D model and/or a texture map of the facility, in other words a digital facility twin, and suggests where to position and how to orientate the sensors (e.g. horizontally and vertically in the facility, angle and direction of orientation), based on the input data.
12 th aspect of “Measuring Patterns”: The Method of any of the preceding aspect of “Measuring Patterns”, comprising the step of:
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Positioning the sensors in the plant growing facility according to similar facility setups stored in a data storage device.
Furthermore, the computing device may be configured to suggest, how long to keep the sensors at the respective places/positions and (if needed/optionally) where to put them for a 2 nd or 3 rd time period to generate a (even more) complete overview of the facility and microclimate within the facility. The suggestions may be based on experience with similar facilities or a calculation how the sensors should be placed on a 3D-grid in the facility to collect data (based on the (spatial) range of the specific sensor). A goal may be to leave a respective sensor as short as possible at a specific location to gather the required data.
The computing device (platform) is configured to suggest the positioning for the sensors based on the farm layout and size. It is also configured to suggest the minimum requirements of sensor data acquisition for a given agricultural system so that for each growth stage and plant maturity the acquired farm data can be considered representative for the digital facility twin database. It is preferred to collect the relevant data as fast as possible so that the farm is “understood and approved” by and for the controlled agricultural system (i.e. as a first/initial setup).
13 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, further comprising the step of including the range of the sensors into the calculation of the positions of the sensors.
14 th aspect of “Measuring Patterns”: The Method of any of the preceding aspects of “Measuring Patterns”, further comprising the steps of
Measuring and collecting data by means of the sensors; Analyzing the measured and collected data and suggesting a re-positioning of the sensors to improve the measurements by means of the computing device.
As mentioned already, this element of the disclosure also relates to a Controlled Agricultural System:
15 th aspect of “Measuring Patterns”: A Controlled Agricultural System configured for performing a method according to any of the preceding aspects of “Measuring Patterns”.
The controlled agricultural system may be configured to automatically suggest missing sensors or how additional sensors could help to accelerate/improve/optimize the growth process. For example, if an array of humidity sensors, or a single humidity sensor, is moved over time across an agricultural system, and detects conditions promoting fungi growth, the system might suggest deployment of camera-based detectors in order to catch the issue before it spreads.
The controlled agricultural system may also be configured to show tutorials how to correctly install and use the different sensors. Once the data of a location (of a sensor) is collected, the system/platform informs the grower and suggests the next possible sensor location.
For short or temporary measurements, drones, other mobile robots (automated agricultural vehicles AGV) or humans may also be used to create/collect the sensor data.
When the initial setup is done, i.e. the controlled agricultural system “understands” the different regions of the facility, the controlled agricultural system is able to suggest placing/permanently installing the sensors in relevant/problematic zones.
Furthermore, the computing device of the controlled agricultural system may also be configured to show the locations of the sensors in a kind of “heat maps” to constantly monitor these locations. If different seasons are to be considered, seasonal maps may be relevant/comprised.
The sensors can also be used to assess the status of the equipment of the plant growing facility and to plan for maintenance or crop rotation (bringing the plants in another area of the facility if the maintenance can affect the yield).
The Sensors may also be able to change their position during the growth of the plants (e.g. angle of inclination or height above ground for positioning). The sensors may also be included in the earth/ground or in the water. The sensors may also be configured to provide real-time data about growth—for example growth of fruits in kg/m 2 /day.
During the execution of the plant-growing project, all relevant data are acquired and considered/analyzed. For instance, the controlled agricultural system may establish all relevant documentation, e.g. in a project report, regarding input factors used and results achieved, including for example agricultural risk assessments. Additionally, post-harvest measurements and risk assessments may be executed and documented as well. The data may be transferred via software interfaces automatically, e.g. stored on the platform.
16 th aspect of “Measuring Patterns”: A computer program product, comprising:
a plurality of program instructions, which when executed by a computer system of a Controlled Agricultural System according to the 15 th aspect of “Measuring Patterns”, cause the Controlled Agricultural System to execute the Method according to any one of the 1 st to 14 th aspect of “Measuring Patterns”.
17 th aspect of “Measuring Patterns”: An agricultural facility (plant growing facility, (vertical) farm, greenhouse, etc.) with at least one Controlled Agricultural System according to the 15 th aspect of “Measuring Patterns”.
“Light Recipes & Workflow”
Horticulture facilities like greenhouses and vertical farms are getting more and more automated. An interesting approach discussed here is to move the plants through the horticulture/agricultural facility, namely to transport them through the facility depending on the specific growth phase. Therein, different light or growth recipes can be applied in different zones along the workflow (and thus plant flow). The recipes can be pre-designed in terms of the respective plant type and growth phase. Each recipe can define a specific lighting scenario, e.g. regarding the intensity and spectral composition, adapted to the growth phase of the plants in the respective zone. As discussed below, also other parameters, like temperature, humidity, air flow, etc., can be customized in the different zones.
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This element of the disclosure is about designing and operating a plant production line of an agricultural facility, and it also relates to the production line and facility itself.
1 st aspect of “Light Recipes & Workflow”: A Method for designing an agricultural facility for growing plants, the method comprising the steps of
determining a number N of different grow scenarios to be applied to the plants in different growth phases GP n (n=2 . . . N); dividing the facility into N zones Z n ; assigning to each of the N zones an area A n ;
wherein a sum, derived from summing up all areas A n , is smaller than or equal to a total growth area available in the agricultural facility (ΣA n total growth area);
and wherein, for at least some of the areas A n , the size of the areas A n is increasing with increasing number n (A n <A n+1 ).
Therein, n is an integral number, and N is greater than 1 (i.e. N=2, 3, 4 or 5); upper limits can for instance be N=50, 40, 30, 20 or 10. The growth of the plants proceeds with increasing number n, so that GP n+1 is the growth phase subsequent to the growth phase GP n (which applies for all values of n from 1 to N). In operation, the plants can be moved through the facility from zone to zone, namely from Z n to Z n+1 , see in detail below.
The grow scenarios can in particular be derived from a growth recipe. These can for instance be or comprise lighting scenarios. In each zone, for instance light fixtures can be adapted to emit light with a spectral composition required by the plants in the actual growth phase. Therein, the light fixtures can be fixed or pre-defined in their respective spectral properties, which can give a cost benefit in comparison to providing light fixtures with adaptable spectral properties, even though a conveyer mechanism or the like is may be required for transporting the plants. Alternatively or in addition to providing specifically adapted light fixtures in the different zones, other actuators for adjusting other environmental conditions (temperature . . . ) can be provided and adapted to the specific zone.
2 nd aspect of “Light Recipes & Workflow”: The Method according to the 1 st aspect of “Light Recipes & Workflow”, wherein, for some of the areas A n , the size of the areas A n remains unchanged with increasing number n (A n =A n+1 ).
Typical growth phases can for instance be germination, growth and maturation. Depending on the specific plant type, there may be growth phases in which the size of the plants remains unchanged. Accordingly, some of the zones Z n can have the same area A n . For instance, in case that the size of the plants remains basically unchanged during maturation, the zones for maturation and growth can have the same size. On the other hand, providing different zones while the size remains unchanged can be advantageous, as for instance growth and maturation may require a different illumination.
3 rd aspect of “Light Recipes & Workflow”: The Method according to the 1 st or 2 nd aspect of “Light Recipes & Workflow”, wherein the zones Z n are arranged in the facility in such a way, that a length of a production line connecting the different zones Z n is minimized.
This optimization can be done for instance numerically, comparable to solving a “Travelling salesman problem”. Apart from minimizing the length of the production line, other boundary conditions can be the accessibility of the plants in the different growth phases, in particular after maturation/fructification. Further, when arranging the zones in the farm, not only the size but also the shape of the building can be taken into account.
4 th aspect of “Light Recipes & Workflow”: The Method according to the any of the preceding aspects of “Light Recipes & Workflow”, wherein the area A n of a respective zone Z n is determined depending on a space factor, namely the space assigned to a plant in the specific growth phase GP n .
The larger the space factor (the more space assigned to a plant), the larger A n .
5 th aspect of “Light Recipes & Workflow”: The Method according to the any of the preceding aspects of “Light Recipes & Workflow”, wherein the area A n of a respective zone Z n is determined depending on a time factor, namely the time a plant is kept in the specific zone Z n .
The larger the time factor, namely the longer the plant is kept in the specific zone Z n , the larger A n .
The method described here can be in particular a computer implemented method. It can for instance be a program part of a light recipe design tool (LRDT) software program.
6 th aspect of “Light Recipes & Workflow”: A Controlled Agricultural System, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, particularly a plant growing facility and/or an hydroponics facility, comprising:
an actuator device for moving plants along a plant production line according to a workflow, the plant production line being grouped into a number of N zones Z n (Z 1 . . . Z N ), wherein N is an integral number greater than 1 (i.e. 2, 3, 4, . . . ); a number of N groups of agricultural light fixtures, the agricultural light fixtures of each one of the groups being arranged to illuminate a dedicated zone, respectively (i.e. group 1 illuminates zone 1, group 2 illuminates zone 2, etc.); a data storage device (e.g. platform/cloud) for storing data comprising the agricultural light fixtures, light recipes for the plants and the workflow, a computing device, configured to control the agricultural facility by means of the actuator device and agricultural light fixtures according to the workflow.
7 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System of the 6 th aspect of “Light Recipes & Workflow”, the Agricultural System being designed in a Method according to any of the 1 st to 5 th aspect of “Light Recipes & Workflow”.
8 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System of the 6 th or 7 th aspect of “Light Recipes & Workflow”, wherein the light fixtures have a specific, fixed spectrum.
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9 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System of any of the 6 th to 8 th aspect of “Light Recipes & Workflow”, wherein the light fixtures have a specific, fixed intensity.
Further, also other photometric values (see above), which are deployed at various stages of the workflow (growth phases), can be fixed. For example, a horticulture light fixture may be deployed at the beginning of the production/workflow configured to provide a specific light spectrum, e.g. for the initial growth phase of the respective plant species. Along the workflow (in different zones of the facility), horticulture light fixtures with other specific, fixed spectra and intensities may be deployed (according to the needs of the plants in subsequent growth phases). With this approach, maximum use of the functionalities of and investment in the agricultural/horticultural facility is ensured. The various fixed spectra may be selected based on plant need, environmental conditions and other requirements (user demands, Bio-mass to be produced, time to harvest, etc.).
An agricultural/horticultural light fixture that offers a fixed spectrum may include means for dimming the spectral intensity. In addition, the geometrical layout of an agricultural light fixture and beam spread are important features. All these features of those light fixtures may be stored in a database (local, cloud) available to users via a platform. The distance between light fixtures and plants (canopy) may also be taken into consideration for a suited agricultural/horticultural facility layout/setup.
The controlled agricultural system according to this element of the disclosure further comprises a computing device, which may be based locally (on-site) or in a (centralized) network or the cloud. The computing device may be configured to be able to run the LRDT software program. The computing device may also have access to the database containing data about the features of the agricultural light fixtures of the controlled agricultural system.
10 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System according to any of 6 th to 9 th aspect of “Light Recipes & Workflow”, wherein the actuator device further comprises actuators able to adjust growth parameters of the plants, e.g. water, nutrients, light (intensity, spectrum), humidity, temperature, air ventilation, water circulation, pesticides.
11 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System of any of the 6 th to 10 th aspect of “Light Recipes & Workflow”, the Agricultural System being configured to provide, in addition to the illumination with the light fixtures, in at least one of the Zones Z n a defined temperature, humidity and/or CO 2 level.
The computing device may be configured to control the agricultural facility by means of the actuators, light fixtures, etc., according to the workflow.
12 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System according any of the 6 th to 11 th aspect of “Light Recipes & Workflow”, further comprising a sensor device able to measure distinctive characteristics of the plants, particularly for detecting the growth status of the plants.
The sensors may sense the growth status/growth phase of the plants as well as a health status of the plants. Health checkpoints along the flow paths can be planned/suggested by the LDRT and implemented into the horticultural plant layout and function.
13 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System according to any one of the 6 th to 12 th aspect of “Light Recipes & Workflow”, wherein the computing device is further configured to trigger the next step of the workflow and/or synchronize the workflow with the growth status of the plants.
14 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System according to any one of the 6 th to 13 th aspect of “Light Recipes & Workflow”, further configured to track and/or monitor the plants during the workflow, e.g. by using a distributed Blockchain ledger method.
The entire through-put cycle of a specific plant can be monitored and correlated with this specific plant, for example by using a distributed Blockchain ledger method thus allowing that the entire treatment cycle of each (individual) plant as well as the plant's health condition is documented accurately and permanently.
15 th aspect of “Light Recipes & Workflow”: The Controlled Agricultural System according to any one of the 6 th to 14 th aspect of “Light Recipes & Workflow”, wherein the data storage device further comprises data about the agricultural facility including its equipment (e.g. layout, size, placement of light fixtures, actuators, sensors, etc.) and growth recipes for the plants.
To facilitate this approach, the present element of the disclosure further proposes a Light Recipe Design Tool (LRDT), which is a software program with executable program steps. In the LRDT, the facility layout and the workflow are inserted (per upload of layouts or pictures, grouping of zones/production stages, insert of dwell (delay or rest)) times, etc.). Furthermore, user demand (bio-mass), post-harvesting treatment, environmental conditions, can be factored in. The LRDT is connected to a database of light recipes for a variety of plants, growth stages, dwell times, On-Off-cycle, and the like, including the light fixture-related and light fixture-plant related data sets (see above).
16 th aspect of “Light Recipes & Workflow”: A method for agricultural management, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, e.g. a plant growing facility, comprising:
at least one controlled agricultural system according to one or more of the 6 th to 15 th aspect of “Light Recipes & Workflow”, and the steps of
Uploading the layout of the agricultural facility and the workflow into the data storage device;
Entering data of user demand (e.g. plant species) into the data storage device;
Fetching a light recipe appropriate for the user demand, including the light fixture-related and light fixture-plant-related data sets from the database stored on the data storage device;
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Rendering a light recipe design (LRD) by proposing a setup of the facility including its equipment (light fixtures, actuators, sensors, etc.), which setup is adapted to the fetched light recipe and the workflow, by means of the computing device based on the data of the previous steps.
The LRDT is configured to develop a light recipe design (LRD) for the entire plant treatment time for the grower's facility. This means the LRDT is configured to take into account the size of the facility, the size of the plants in each growth stage (growth phase), the time the plants remain in each grow stage, the number of grow stages and the like (see above). Based on this, the LRDT proposes a setup for the facility, indicating the space required for each grow stage, where to put light fixtures and which types of light fixtures including the respective configuration (spectrum, intensity). It also defines the appropriate velocity (or stand-still time) of plants that may move on a track or conveyor belt from one position to another. It also defines the appropriate horticultural fixture design, layout, placement of attached or connected optical components (like lenses, reflectors, light guides), cooling conditions, airflow and the like, distance to the plant canopy, as well as any inclination of the light fixture.
17 th aspect of “Light Recipes & Workflow”: The method for agricultural management according to the 16 th aspect of “Light Recipes & Workflow”, further comprising the steps of
Implementing the light recipe design (LRD) in the facility;
Controlling the workflow in the facility by means of the actuator device and the computing device based on the LRD.
The LRD may be uploaded to the grower's horticulture Internet of Things (IoT) platform. The horticulture IoT platform may be configured to do real-time asset tracking to monitor the plant movement along the workflow and match it to the LRD and give feedback to the grower if it matches or if something needs to be adjusted to the LRD. Adjustment to the workflow could be for example slowing down/speeding up the process time at a growth stage. Asset tracking may be done for example by sensors and radio frequency (RF), RFID or barcode and QR-code scanning of plant trays or plant pots during the production/workflow.
18 th aspect of “Light Recipes & Workflow”: The method for agricultural management according to the 17 th aspect of “Light Recipes & Workflow”, wherein the step of controlling the workflow further comprises the sub-steps of
Moving the plants along the direction of the workflow and across the zones (Z 1 ; Z 2 ; Z 3 ) of the plant production line;
Controlling the light fixtures according to the light recipe design (LRD), i.e. according to a setup of the facility including its equipment (light fixtures, actuators, sensors, etc.), which setup is adapted to the fetched light recipe and the workflow.
19 th aspect of “Light Recipes & Workflow”: The method for agricultural management according to the 18 th aspect of “Light Recipes & Workflow”, whereby moving of the plants is conducted in order to cross each zone (Z 1 ; Z 2 ; Z 3 ) according to a pre-defined schedule.
20 th aspect of “Light Recipes & Workflow”: The method for agricultural management according to any one of the 16 th to 19 th aspect of “Light Recipes & Workflow”, further comprising the steps of
Measuring and collecting data by means of the sensor device, comprising data for detecting the growth status of the plants, and adapting the timing for moving the plants to the detected status of the plants.
21 th aspect of “Light Recipes & Workflow”: A computer program product, comprising:
a plurality of program instructions, which when executed by a computer system of a Controlled Agricultural System according to any one of the 6 th to 15 th aspect of “Light Recipes & Workflow”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 16 th to 20 th aspect of “Light Recipes & Workflow”.
The LRDT software program may be configured to improve itself based on feedback (customer, produces) by executing Deep Learning or AI methods. The LRDT software program may be licensed to other parties.
22 th aspect of “Light Recipes & Workflow”: An agricultural facility (plant growing facility, (vertical) farm, greenhouse, etc.) with at least one Controlled Agricultural System according to any one of the 6 th to 15 th aspect of “Light Recipes & Workflow”.
Though a horticultural plant facility can have many flow paths, it is preferred to keep it as simple as possible, e.g. following a straight line through the horticultural plant facility (see FIG. 19 ). Plant factories can have a larger number of plant rows and paths, probably many hundred. Flow paths can be stacked upon each other in vertical layers thus providing a 3D path system. In principle, the flow paths could reverse their direction so that the plants move again through a previous light setting (but in opposite direction).
Plant Health/Growth
“Prophylaxis”
According to the element “Prophylaxis” of the disclosure, a controlled agricultural system and a method for agriculture for prevention of diseases and pests or for fighting same is proposed.
To this end, abiotic and biotic environmental parameters are monitored and, if need be, appropriate measures are proposed or, alternatively, introduced automatically.
1 st aspect of “Prophylaxis”: More specifically, a controlled agricultural system, comprises a first sensor device for acquiring data in relation to environmental parameters (environmental data), a data storage device for storing the data from the first sensor device and a computing device configured to analyze the data of the data storage device in order to identify critical situations and propose suitable countermeasures where applicable.
Parts of the controlled agricultural system, for example the computing device or the data storage device may be based locally or else on a network or cloud.
The term environment in this case comprises the greenhouse per se and the region outside of the greenhouse.
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The environmental parameters, i.e., the effective factors, include data (environmental data) such as temperature, wind speed, humidity, light factor, ozone content of the air, UV radiation, but also season or amount of pollen or number of insects in the air. It is likewise possible to monitor the temperature at the leaves of the plant. If the temperature there falls below the dew point, there is then an increased risk of fungi afflicting the plants. As to appropriate measures against such risk, see also the element “Fungi Growth Inhibition” of the group “Plant Health & Growth” of the disclosure.
Therefore, the controlled agricultural system is equipped with sensors that are able to acquire the aforementioned abiotic and biotic environmental parameters at adjustable time intervals or else continuously.
2 nd aspect of “Prophylaxis”: Alternatively, a controlled agricultural system comprises a first sensor device for acquiring data in relation to environmental parameters (environmental data), an actuator device, a data storage device for storing the data from the first sensor device and a computing device configured to analyze the data of the data storage device in order to identify critical situations and introduce suitable countermeasures with the aid of the actuator device where applicable.
Countermeasures could be:
Start automated illumination with specific light treatment (UV)
Start automated spraying of pesticides
Inform the operator to have a check and show the affected or suspicious location
Adjust watering, ventilation, etc.
Further countermeasures could be (the controlled agricultural system may be configured to start them automatically or inform the grower and leave the choice to him):
Low acidity→add an acid to the nutrient solution High acidity→add a base to the nutrient solution Low nutrients→add macro and micro elements or ready to use fertilizer to nutrient solution Temperature too low→tell heat system to adjust it, close or open windows Too dark/bright→open screen/close screen, dim up/dim down light Aphids found→add imidacloprid (or any other insecticide) to nutrient solution Mildew found→change light to a UV enriched spectrum/add fungicide to automated sprayer, adjust humidity and temperature to optimum.
The controlled agricultural system may also be configured to just giving notifications/recommendations in the beginning or wait for confirmation by the operator before executing the recommended countermeasures. For instance, the system may recommend a countermeasure like “In the current situation, grower XYZ implemented this or that countermeasure with the effect of ABC. Do you want to execute?” Alternatively or in an advanced stage of the project the system may be configured to decide and implement countermeasures autonomously.
The measure using pesticides should be execute as described in the user manuals. The user manuals of seed-, substrate-, fertilizer-, pesticide- and equipment companies should be stored and continuously updated in the system.
The countermeasures should also take into account the expected yield/harvesting time (and acceptable reductions or delays). Afterwards the system can give suggestions how often we increase the light intensity, or change the spectrum.
Sometimes it may also makes sense to delay a measure, e.g. before opening and closing the sunscreen to take account for small clouds in the sky.
All countermeasures may be documented by the agricultural system.
3 rd aspect of “Prophylaxis”: The controlled agricultural system according to the 1 st or 2 nd aspect of “Prophylaxis”, comprising a second sensor device for acquiring data in relation to the state of the plants (plant data), wherein the data storage device is configured to store the data from the second sensor device.
Specifically, the controlled agricultural system is equipped with sensors that are able to acquire the state of the plants, in some embodiments/implementations the stress state thereof.
By way of example, these may be optical, chemical or electrical sensors, which identify, for example, the growth of the plants (density of the leaves, height of the plants, plant morphology, leaf area index), measure the color and reflectivity of the leaves, the thermo-luminescence thereof or the chlorophyll fluorescence thereof or the abscisic acid (ABA) luminescence thereof and hence the health of the plants and in particular the stress state thereof, and are able to supply these (plant data) to an evaluation.
Furthermore, the controlled agricultural system is configured to measure the recovery state, i.e., the reduction of stress parameters, of the plants. These information items are stored, in some embodiments/implementations in a plant-specific manner, in a data storage device and are analyzed by a computing device.
If a disease has been detected, the computing device of the controlled agricultural system regularly checks the sensors that detected the disease to monitor the development of the disease. If no improvement of the situation can be observed after a certain time period has passed, a warning is issued. If the situation improves, the countermeasures are modified accordingly, e.g. the amount of insecticide may be reduced.
4 th aspect of “Prophylaxis”: The controlled agricultural system according to the 3 rd aspect of “Prophylaxis”, wherein the computing device is configured to analyze the data of the data storage device, to identify negative effects on the plants in the process and reduce or stop the countermeasures should negative effects on the plants be identified.
The analysis can be performed using methods connected to artificial intelligence (AI), such as deep learning. The goal of the analysis is to identify and/or predict an environmental situation that is accompanied by an increased occurrence of diseases or pest infestation. The analysis may also include the plant state, for example the degree of maturity. This is because, as a rule, the risk of pest infestation also increases with advancing degree of maturity.
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Additionally, situations in which pests such as fungi thrive may arise (particularly indoors) from the growth recipes with variable temperatures and degrees of humidity thereof. These situations may likewise be identified.
If such a situation is identified, the operator of the greenhouse can then be informed so as to introduce measures that prevent or reduce an outbreak of the disease or which prevent pests from entering the greenhouse.
However, the system may also be able to take up these measures in preventative fashion, with care having to be taken that the plants are not adversely affected, or not adversely affected too much, by the measures. Thus, there is a trade-off between potential use and possible damage by the measure. This is weighted with the probability of the occurrence of the disease or the pests and the probability of damage by the measure, and hence a decision is made as to whether or to what extent, the measure is carried out.
5 th aspect of “Prophylaxis”: The controlled agricultural system according to any one of the 1 st to 4 th aspect of “Prophylaxis”, wherein the first sensor device comprises one or more sensors for one of the following environmental parameters or a combination thereof: air composition, air temperature, air humidity, wind speed, light intensity, light spectrum, number of pests, light factor, ozone content of the air, UV radiation.
6 th aspect of “Prophylaxis”: The controlled agricultural system according to any one of the 1 st to 5 th aspect of “Prophylaxis”, wherein the second sensor device comprises one of the following sensors or a combination thereof: temperature sensor, gas analyzer, photodiode, spectrometer, camera.
7 th aspect of “Prophylaxis”: The controlled agricultural system according to any one of the 1 st to 6 th aspect of “Prophylaxis”, wherein the actuator device comprises one or more of the following actuators or a combination thereof: plant light fixture with various light sources, UV radiation source, applicator for pesticides, applicator for herbicides, applicator for fungicides, applicator for useful creatures, mobile robot unit, drone, heater or cooler, ventilator.
Measures may include the irradiation with UV (or generally a change in the light recipe), the closing of windows and doors, the reduction of the humidity or the temperature, or else the automatic release of useful creatures or the automatic application of correspondingly licensed pesticides by means of a mobile robot unit, etc.
Placing UV-reflecting mats below the plants may be a passive measure for reducing the infestation of pests. Thus, pests can no longer distinguish leaves from the ground, and so they settle less frequently on the plants.
Effects on the plants can be monitored by controlling the plant stress (but also by checking the growth with cameras, etc.). If need be, preventative measures may be terminated if the stress on the plants becomes too large. At the same time, environmental parameters are checked regularly to see when the risk of an outbreak of disease or infestation of pests has abated.
8 th aspect of “Prophylaxis”: A method for agricultural management, comprising the following method steps: measuring relevant environmental parameters in a target area, analyzing the measurement data and identifying critical situations such as environmental conditions that are inexpedient for plants, for example, with an (elevated) risk of the plants being afflicted by disease or infested by pests or whether the plants are already afflicted by disease or infested by pests, proposing, or alternatively automatically introducing, countermeasures.
9 th aspect of “Prophylaxis”: The method for agricultural management according to the 8 th aspect of “Prophylaxis”, comprising the following additional steps: a) acquiring data in relation to the state of the plants and checking whether the countermeasures have a (negative) effect on the plants, b) reducing or stopping the countermeasures if the countermeasures have a (negative) effect on the plants, c) re-measuring relevant environmental parameters in the target area and checking whether a critical situation still is present if the countermeasures do not have a (negative) effect on the plants, d) stopping the countermeasures if the situation is no longer critical, e) continuing the countermeasures if the situation still is critical and continuing with step c).
10 th aspect of “Prophylaxis”: The method for agricultural management according to the 8 th or 9 th aspect of “Prophylaxis”, carried out by a controlled agricultural system according to any one of the 1 st to 7 th aspect of “Prophylaxis”.
The method enables to identify critical situations such as environmental conditions that are inexpedient for plants, and optionally taking countermeasures. Furthermore, reference is made to the description above, the features described there shall also be disclosed in terms of the method.
11 th aspect of “Prophylaxis”: A machine-readable computer product, comprising a multiplicity of program instructions which, when executed on the computing device of the controlled agricultural system according to any one of the 1 st to 7 th aspect of “Prophylaxis”, cause the Controlled Agricultural System to execute the method according to the 8 th or 9 th aspect of “Prophylaxis”.
“Stress Detection”
According to the element “Stress Detection” of the disclosure, pests, diseases and stress of plants are detected based on leaf characteristics by means of sensors.
1 st aspect of “Stress Detection”: More specifically, a controlled agricultural system, comprises a sensor device able to measure distinctive characteristics of plants (measured data of plants), a data storage device for storing reference data of plants, and a computing device, configured to compare the data measured by the sensor device with the respective reference data stored on the data storage device and to identify stress, diseases, pests or any other critical condition of the plants from the result of the comparison.
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Furthermore, the controlled agricultural system comprises a computing unit configured to identify stress or disease from the data measured by the sensors. For instance, if the computing unit detects morphological changes of the leaves, the controlled agricultural system delivers a warning to the user (farmer).
2 nd aspect of “Stress Detection”: The controlled agricultural system according to the 1 st aspect of “Stress Detection”, further comprising a user interface for delivering the result of the comparison and/or identification to the user.
To this end, the controlled agricultural system comprises sensors, which are able to measure distinctive characteristics of plants, e.g. color changes of the leaves by means of optical sensors (e.g. sensors for spectral measurements), plant morphology by means of a camera, etc.
In an exemplary embodiment, a camera is configured to take pictures of the leaves in regular intervals (e.g. minutes, hours, days). The pictures are then compared to earlier pictures or pictures of a healthy plant. “Earlier pictures” can mean that one or a sample of earlier pictures have been taken for the purpose of later comparison or that an average of the earlier pictures has been calculated with respect to the respective parameters like inclination, leaf-size, roll-up, etc.
A stress situation can be detected, if the picture analysis shows a difference in certain morphology parameters which are larger than a certain threshold, for instance:
certain inclination of the leaf (e.g. the leaf in inclined downwards, although it shows upwards for healthy plants), a roll-up of the leaf (i.e. the tip of the leave moves upwards), curling of leaves (i.e. the edges of the leaf move towards each other like folding the leaf longitudinally), an unsymmetrical leaf-size, i.e. one side of the leaf is smaller e.g. by at least 10 percent than the second side, or the size has been reduced by a certain amount (e.g. 10 percent) compared to earlier pictures, deformation due to an infection by aphids or other insects.
3 rd aspect of “Stress Detection”: The controlled agricultural system according to the 1 st or 2 nd aspect of “Stress Detection”, further comprising an actuator device.
4 th aspect of “Stress Detection”: The controlled agricultural system according to the 3 rd aspect of “Stress Detection”, wherein the actuator device comprises one or more of the following actuators or a combination thereof: agricultural lighting device, radiation source able to emit ultraviolet (UV) radiation, irrigation system, ventilation system, heating/cooling system, feeder for dosing fertilizer and/or pesticides.
If the morphological change is due to a certain root cause (e.g. not enough water), the system may optionally initiate a counter-measure (e.g. irrigation). For this purpose, the controlled agricultural system further comprises respective actuators (e.g. irrigation system).
5 th aspect of “Stress Detection”: The controlled agricultural system according to the 3 rd or 4 th aspect of “Stress Detection”, wherein the computing device is configured to automatically counteract by means of the actuator device, if stress, diseases, pests or any other critical condition is identified.
For identifying stress or disease, the pictures currently taken may be compared with existing reference pictures of corresponding plants in good health and condition retrieved from a database. The database is stored in a data storage device that may be based locally, in a network or the cloud. The identification process may be performed by using picture recognition algorithms, e.g. deep learning. By using data of other sensors (environmental sensors, chemical sensors), the different morphological changes can be linked to other causes (e.g. hanging leafs due to not enough water or due to other environmental parameters such as a too high salt concentration). These causes may also depend on the specific kind of plant, which may also be taken into consideration when analyzing the pictures. Artificial Intelligence programs may be used to monitor, collect and interpret such sensor generated data and calculate forecast or prediction models in order identify and reduce plant stress.
6 th aspect of “Stress Detection”: The controlled agricultural system according to any one of the 1 st to 5 th aspect of “Stress Detection”, wherein the sensor device comprises one or more of the following sensors or a combination thereof: imaging system, e.g. still or video camera, in some embodiments/implementations TOF camera or stereo camera, LIDAR system, environmental sensor, e.g. for measuring temperature, humidity and/or chemical composition of the air or soil, sensors for detecting color changes of the plant, particularly of the leaves, sensors for detecting specific gases exhaled by the plants, sensors for detecting the fluorescence emitted by the plants after activation with dedicated radiation.
In a preferred embodiment, the measurement system is capable to create a 3D-representation of the leaves (e.g. by using time of flight (TOF-) cameras, stereo cameras, or LIDAR (light detection and ranging)). If the picture is only available in two dimensions, the angle of inclination or the symmetry of the leaf might be misinterpreted, as the cameras cannot look perpendicularly on each leaf. A 3D-representation helps to avoid this mistake.
In a similar way, root morphology (e.g. in hydroponics systems) can be measured and analyzed with regard to pests or diseases.
Furthermore, a method for agricultural management detects pests, diseases and stress of plants based on leaf characteristics as described above.
7 th aspect of “Stress Detection”: A method for agricultural management, comprising at least one controlled agricultural system as described above and the following method steps: measuring distinctive characteristics of plants in a target area by means of the sensor device and collecting these measured data of the plants, storing reference data of plants, comparing the measured data with the reference data by means of the computing device and identifying stress, diseases, pests or any other critical condition of the plants from the result of the comparison by means of the computing device.
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8 th aspect of “Stress Detection”: The method for agricultural management according to the 7 th aspect of “Stress Detection”, further comprising the step of delivering the result of the comparison and/or identification to the user by means of the user interface.
9 th aspect of “Stress Detection”: The method for agricultural management according to the 7 th or 8 th aspect of “Stress Detection”, further comprising the step of counteracting automatically by means of the actuator device, if stress, diseases, pests or any other critical condition of the plants is identified.
10 th aspect of “Stress Detection”: The method for agricultural management according to any one of the 7 th to 9 th aspect of “Stress Detection”, further comprising the step of establishing reference conditions before measuring distinctive characteristics of the plants in the target area, in some embodiments/implementations establishing reference lighting of the plants in the target area.
In addition, to gain consistent results the measurement should be conducted under standardized conditions, as different illumination (color or intensity) may affect the leaf morphology as well. In addition, different measurement conditions, e.g. colors of the luminaires, might lead to different measurement results. On the other hand, well-defined changes of illumination parameters can be used to analyze the plant stress, as it might induce changes in the leaves. This change, especially the reaction time for a respective change, can be measured and the measurement result may provide an indication about the stress.
11 th aspect of “Stress Detection”: A machine-readable computer product, comprising a multiplicity of program instructions which, when executed on the computing device of the controlled agricultural system according to the 1 st to 6 th aspect of “Stress Detection” causes the controlled agricultural system to execute the method according to any of the 7 th to 10 th aspect of “Stress Detection”.
“Discolored Spots Detection”
According to the element “Discolored Spots Detection” of the disclosure, diseases and stress of plants are detected based on the detection of discoloration by means of complementary illumination. Additionally, complementary illumination may be used to identify colors or color changes, for example, due to ripening.
1 st aspect of “Discolored Spots Detection”: A controlled agricultural system, particularly for detection of plant diseases and various stages of ripening, comprising a data storage device comprising data, which are related to spectra of light, particularly of light with colors complementary to colors of parts of plants (Complementary Color Spectrum CCS), for example, complementary to discolored areas or parts of plants, an illumination device able to emit light with a color spectrum according to the data stored in the data storage device and illuminate plants, a sensor device able to detect the light reflected by the illuminated plants, and a computing device, configured to control the illumination device based on the data of the database, and further configured to analyze the data from the sensor device and detect dark areas on the plants.
2 nd aspect of “Discolored Spots Detection”: A controlled agricultural system, particularly for detection of plant diseases and various stages of ripening, comprising an illumination device able to emit light, perform a spectral light scan, comprising Complementary Color Spectra, particularly with regard to discoloration of plants or plant parts, and illuminate plants a sensor device able to detect the light reflected by the illuminated plants, a computing device, configured to control the illumination device for performing a spectral light scan, and further configured to analyze the data from the sensor device and detect dark areas on the plants.
For instance, various Discolored Spots (DSi) are illuminated with light with Complementary Color Spectra (CCSi). If all Discolored Spots (DSi) show the same discoloration, they may be illuminated with the same Complementary Color Spectra (CCSi). If the Discolored Spots (DSi) show different discolorations, they may be illuminated with different Complementary Color Spectra (CCSi), corresponding to the different discolorations.
The detection of discoloration may be used for various tasks of cultivating plants. For instance, it may be used to track changes in plants or part of the plants, e.g. flowering, changing colors due to ripening etc. In this case, the complementary color of the state of the plant is applied (either the previous state to see if it is still there or the expected state to see if it has been realized). For example, to verify if the color of the tomatoes have already changed from green to red, the tomatoes may be illuminated with light of the color complemental to green (i.e. reddish light (magenta)). If such illuminated tomatoes appear dark, their color is still green. Otherwise, they have already changed their color to red and may be ready for harvesting. Alternatively, the tomatoes may be illuminated with light of the color complemental to red (i.e. cyan). If the illuminated tomatoes appear dark, their color is already red. Otherwise, their color is still green.
In the following, the disclosure will be described in more detail for the example of detecting diseases, where plants show discolored spots. However, the method steps and features may as well be used for other tasks of breeding, cultivating and/or harvesting plants, such as, inter alia, the examples described above.
A discolored spot, in the following designated Discolored Spot DSi, where i is the index of the spot of the plant, comprising stem, petals, etc. (i=1 to N, wherein N is the total number of spots of the respective plant) shows, when lit with white light (e.g. a white light source with a reference light spectrum that shows a good Color Rendering Index CRI (in some embodiments/implementations higher than 90), or a standardized light source with a specific reference light spectrum) a reflection light (light remission) with a color/spectrum that is different from the reflection light of a non-discolored plant area or spot.
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Specifically, any Discolored Spot DSi does not reflect light with a complementary spectrum (called: Complementary Color Spectrum CCSi) This means that e.g. a yellow spot on a leaf does not (or only minimally) reflect blue light. It is preferred that the spectral Full Width at Half Maximum (FWHM) of the complementary spectrum is rather narrow, in some embodiments/implementations in the range between 1 nm, and 50 nm.
The current (local) color of a discolored spot DSi is termed Discoloration Color DCi. A plant can have several (local) Discoloration Colors DC 1 , DC 2 . . . DCN, one Discoloration Color DCi for each Discolored Spot (DSi).
The Complementary Color Spectrum CCSi of each of the respective Discolored Spots DSi are provided by a Complementary Light Source CLSi. A horticulture light fixture may comprise several Complementary Light Sources CLSi.
It may be preferred that the illumination system (e.g. horticulture light fixture) emits only one Complementary Color Spectrum CCSi at a given time thus making it easier for sensor systems to differentiate between various reflected light colors. However, it may also be preferred to simultaneously apply radiation (light) with two or more Complementary Color Spectra CCSi to the plants. Then a detecting camera system needs to comprise color separation filters or other means of differentiating the various Complementary Color Spectrum CCSi.
3 rd aspect of “Discolored Spots Detection”: A controlled agricultural system, according to the 1 st or 2 nd aspect of “Discolored Spots Detection”, wherein the illumination device comprises light sources, which are able to emit light of at least three different colors, in some embodiments/implementations red, green and blue.
In a preferred embodiment, the illumination unit comprises at least three light colors, e.g. red, green and blue for the RGB color-space. Such illumination units are more and more frequently used in agricultural systems for illumination purposes, but the illumination unit to detect the discolored spots/disease may also be added as an independent light source. For example, the illumination unit may be arranged in the agricultural lighting system or a separate fixed installation, or in a moveable installation, e.g. on tracks or in in automated guided vehicle (AGV) or even inside a flying drone.
4 th aspect of “Discolored Spots Detection”: A controlled agricultural system, according to any one of the 1 st to 3 rd aspect of “Discolored Spots Detection”, wherein the sensor device comprises one or more of the following sensors: camera, CCD sensor with or without filter, photodiode.
Due to the above explained measures according to the disclosure, and because the discolored spots DSi do not reflect (or only very minimally) light with their respective Complementary Color Spectrum CCi, discolored spots are visualized as dark spots that can be recognized and measured easily by a camera or other sensor systems (Photodiode, CCD chips with filters etc.).
In other words, when a plant has discolored parts/spots due to a disease or any other cause, illuminating the plant with the complementary light increases the contrast between the discolored part and the surrounding part of the plant/stem/leave, making it easier to identify discolored parts/spots.
In some embodiments/implementations, the controlled agricultural system according to the disclosure comprises a (scientific) database with a mapping of plant diseases, diseases-typical discolorations of the plants (for every growth stage), and the respective complementary light (Complementary Color Spectrum CCSi). The database is part of a computing device.
The controlled agricultural system further comprises an illumination unit (lighting fixture), which may be based on LEDs (with or without phosphor conversion), Super-Luminescent Diodes, or lasers, and which emits light in the visible range (approx. 380 to 780 nm), and may also include violet and Far-Red radiation. The illumination unit is suited to apply the complementary light (Complementary Color Spectrum CCSi). The controlled agricultural system is configured to control the illumination unit based on the data of the database.
The controlled agricultural system further comprises a sensor system (controlled by its control unit). This may be a (still or video) camera. For each setting of complementary light, the camera takes a picture of the plants (probe picture). The computing device analyses each picture and looks for dark spots. The computing device may also store a picture taken with normal/reference illumination, e.g. white light, which shows the leaves and other parts of the plants (reference picture). The computing device then compares each probe picture with the respective reference pictures. If dark spots are detected in an area, which comprises parts of the plants, this may indicate a discoloration due to a disease.
Based on the data of the database, which may be stored on a data storage device connected to (or integrated within) the computing device, the controlled agricultural system applies to the plants complementary light through the illumination unit. For instance, red discolorations (with an RGB-code of e.g. #FF0000) will appear dark when illuminated with a cyan color (with the RGB-code of #00FFFF). Therefore, this measure according to the disclosure intensifies the contrast between the discolored part and the normal-colored part and makes it easier to detect a discolored part/spot (disease).
In a second embodiment, the controlled agricultural system applies normal (reference), non-complementary light of the discoloration to the plant in a first step and then the complementary light in a second step. This will lead to a very pronounced color difference between the first (reference) and the second (probe) picture taken with the camera, making it even easier to detect discolored parts.
In another embodiment of the disclosure, the illumination unit illuminates the plants at different wavelengths (each wavelength range is emitted consecutively, i.e. only during separate time intervals), i.e. performs a spectral scan mode for probing discolored areas, and the computing device analyses the pictures. This approach can be advantageous to detect possible diseases if the database, particularly the data for specific Complementary Color Spectra, is not available or incomplete.
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In yet another embodiment, the computing device is configured to trigger measurements of discolorations in regular or irregular time intervals or even stochastically. The measurement data may be analyzed by means of deep learning algorithms. Furthermore, the results of the analysis may be represented graphically. Such procedure may be used to monitor curing of plant diseases.
5 th aspect of “Discolored Spots Detection”: A controlled agricultural system, according to any one of the 1 st to 4 th aspect of “Discolored Spots Detection”, further comprising a user interface.
The computing device may also comprise a user interface, which provides feedback of the measurements to the user. Via the interface the user can also schedule measurements (once a day, once a week, during the day, at the end of the day, irregular intervals, stochastically within time intervals, etc.). The computing device then interrupts the normal illumination mode and switches the illumination to detect mode.
In the detect mode, the plants are illuminated with complementary light, either applying the lights (Complementary Color Spectra) stored in the database or providing a spectral light scan, as described above. If the detection is performed in a greenhouse, the controlled agricultural system may draw down shutters or blinds prior to starting the detection mode. For this purpose, the controlled agricultural system may further comprise an appropriate actuator.
Due to the enhanced contrast between the dark spots and the surrounding when taking pictures with complementary light, diseases can be easily detected. It is not even necessary to have a very close look at the plants, but the sensor (e.g. the camera) can be placed at some distance of a plant and cover several plants at the same time. The plants can be illuminated and sensed from above or from the side (i.e. focusing on leaves or stems).
It should be noted that the controlled agricultural system according to the disclosure that applies to the plants complementary light by means of the illumination unit can be used in a greenhouse that is with the presence of natural sun light, as well as in a completely enclosed farming environment (controlled agricultural environment). In the first case, illumination with complementary light will still increase the color difference between healthy and discolored unhealthy plant parts. Similarly, in the second case, when the regular illumination light is on (ON-Lighting-cycle) or OFF (OFF-lighting-cycle). If measurements are performed in the ON-Lighting-cycle, the regular illumination can be temporarily switched off during the measurement cycles and switched on afterwards.
Agricultural lighting fixtures may comprise artificial light sources like Light Emitting Diodes (LED) with or without conversion by using a fluorescent substance, commonly referred to as phosphor, monochromatic Laser diodes, OLED light emitting material on organic basis, Quantum Dot light emitters, Fluorescent lamps, Sodium low and high pressure lamps, Xenon and Mercury Short Arc lamps, Halogen lamps, and the like.
All of the plants arranged in an agricultural or horticultural facility and managed by means of a controlled agricultural system according to the disclosure need not be illuminated with the Complementary Color Spectra (CCSi) at the same time, but can be illuminated sequentially. For example, the light with a Complementary Color Spectrum (CCSi) may be directed onto a scanning device, like a moving MEMS-mirror, and then reflected onto the various parts of an agricultural plant environment (plant cultivating area) in a time sequential manner.
6 th aspect of “Discolored Spots Detection”: A controlled agricultural system, according to any one of the 1 st to 5 th aspect of “Discolored Spots Detection”, further comprising an actuator device able to treat the plants, e.g. with water, UV-light, IR-light, nutrition, medication, fungicides, pesticides.
Furthermore, the computing device may comprise an object recognition program that determines the location of the affected plant and can then send command controls to a health sustaining system. The health sustaining system may comprise appropriate actuators, e.g. by means of automated guided vehicles (AGV), which then treat the affected plant(s) (or plant area) with e.g. UV-light, IR-light, nutrition, medication, pesticides, etc.
7 th aspect of “Discolored Spots Detection”: A controlled agricultural system, according to any one of the 1 st to 6 th aspect of “Discolored Spots Detection”, wherein the colors of parts of plants comprise one or more of the following: discolored spots, particularly due to diseases, colors of flowers, colors of fruit in various stages of ripening.
Furthermore, according to “Discolored Spots Detection”, a method for detecting/verifying colors or discoloration of plants, or discolored spots on plants, or discoloration of plant parts, like fruits or flowers, is proposed by providing an illumination system that illuminates the plants or parts of the plants with light with Complementary Color Spectra (CCSi) with regard to the anticipated color or discoloration of the plant, plant part or plant spot. The controlled agricultural system is configured to be able to execute the method.
8 th aspect of “Discolored Spots Detection”: More specifically, the method for agricultural management, comprises at least one controlled agricultural system and the steps of starting the detect mode of the controlled agricultural system, illuminating plants with complementary light by means of the illumination device, and screening/detecting the plants for dark areas, e.g. discolored spots that appear as dark spots when illuminated by the complementary light, by means of the sensor device.
9 th aspect of “Discolored Spots Detection”: The method for agricultural management according to the 8 th aspect of “Discolored Spots Detection”, further comprising the step of analyzing and identifying the cause of a detected dark area, e.g. a discolored spot, flower, fruit, etc., by means of the computing device based on data store on the data storage device.
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10 th aspect of “Discolored Spots Detection”: The method for agricultural management according to the 8 th or 9 th aspect of “Discolored Spots Detection”, further comprising the step of identifying the disease associated with a detected discolored spot by means of the computing device.
11 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 8 th to 10 th aspect of “Discolored Spots Detection”, wherein screening the plants for dark areas further comprises the step of taking pictures of the plants by means of the camera.
12 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 8 th to 11 th aspect of “Discolored Spots Detection”, wherein screening the plants for dark areas further comprises the step of detecting the color of the light reflected by the plants/plant parts by means of at least one photodiode or CCD chips with filters.
13 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 8 th to 12 th aspect of “Discolored Spots Detection”, further comprising the step of probing for a specific discoloration by illuminating the plants with the respective complementary light.
14 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 8 th to 13 th aspect of “Discolored Spots Detection”, further comprising the step of enhancing the contrast for analyzing and detecting the dark areas by illuminating the plants with normal/reference light, particularly white light, and comparing the measurement data (reference data) from the sensor device with the respective measurement data (probe data) from the illumination with complementary light.
15 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 10 th to 13 th aspect of “Discolored Spots Detection”, further comprising the step of taking countermeasures against the identified disease, e.g. treating the affected plant(s) with e.g. UV-light, nutrition, medication, fungicides, pesticides, etc., by means of the actuator device.
16 th aspect of “Discolored Spots Detection”: The method for agricultural management according to any one of the 10 th to 13 th aspect of “Discolored Spots Detection”, further comprising the step of informing the user by means of the user interface that discolored spots have been identified and about the diagnosed disease.
Furthermore, reference is made to the description above; the features described there shall also be disclosed in terms of the method.
17 th aspect of “Discolored Spots Detection”: A machine-readable computer product, comprising a multiplicity of program instructions which, when executed on the computing device of the controllable agricultural system according to any one of the 1 st to 7 th aspects, cause the Controlled Agricultural System to execute the method for agricultural management according to any one of the 8 th to 16 th aspects of “Discolored Spots Detection”.
18 th aspect of “Discolored Spots”: A method for investigating a plant grown in an agricultural system, comprising:
providing a complementary light source for emitting a first complementary light with a first complementary color spectrum, which has a first spectral gap in comparison to a white light spectrum, illuminating the plant with the first complementary light, screening the plant illuminated by the first complementary light for dark areas, which absorb the first complementary light at least partly, and/or for bright areas, which reflect the first complementary light at least partly.
19 th aspect of “Discolored Spots”: The method of the 18 th aspect of “Discolored Spots”, wherein the first spectral gap of the first complementary color spectrum lies in the green and/or yellow spectral range, the plant illuminated by the first complementary light being screened for bright areas.
Typical leaves having a green color show no absorption in the green/yellow spectral range. Consequently, they reflect green/yellow light, which is the reason for their green appearance. When illuminating the plant with spectral intensities outside the green/yellow spectral range, the focus is not on the green leaves themselves but on any discoloration of the leaves, for instance discolored spots. Those can indicate an insufficient supply or a disease of the plant. In simple words, since the green colored leave itself is not illuminated in its spectral range, any discoloration of the leaves can be detected better. Any discoloration appears brighter as the green background is reduced.
“Blue spectral range” can for instance mean a spectral range from 400 nm to 490 nm.
“Green spectral range” can for instance mean a spectral range from 490 nm to 575 nm.
“Yellow spectral range” can for instance mean a spectral range from 575 nm to 600 nm.
“Orange spectral range” can for instance mean a spectral range from 600 nm to 650 nm.
“Red spectral range” can for instance mean a spectral range from 650 nm to 800 nm.
The existence of a “spectral gap” does not necessarily mean that there is no intensity at all in the respective spectral range. The intensity shall be at least reduced, it can for instance amount to not more than 30%, 20% or 10% of a maximum intensity of the complementary color spectrum (comparing for instance the spectral irradiance). This can apply for an average intensity in the spectral range with the spectral gap and/or for a maximum intensity in the spectral range with the spectral gap. Nevertheless, it is also possible that there is no intensity at all in the spectral range with the gap.
20 th aspect of “Discolored Spots”: The method of the 19 th aspect of “Discolored Spots”, wherein leaves of the plant illuminated by the first complementary light are screened for the bright areas for detecting a plant disease or inappropriate plant treatment.
Alternatively, the screening of bright areas can also allow for a tracking of a growth stage, for instance the flowering or ripening (e.g. change from green to red color).
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21 st aspect of “Discolored Spots”: The method of the 18 th aspect of “Discolored Spots”, wherein the first spectral gap of the first complementary color spectrum lies outside the green spectral range, the plant illuminated by the first complementary light being screened for dark areas.
In this case, for instance, the green leave itself will reflect the green light and appear bright, whereas a discolored area will appear dark when the spectral gap lies outside the spectral range reflected by the discoloration.
22 nd aspect of “Discolored Spots”: The method of the 21 st aspect of “Discolored Spots”, wherein the first spectral gap of the first complementary color spectrum lies in the blue spectral range.
The first complementary color spectrum can have intensities in the green and/or yellow and/or orange and/or red spectral range.
23 rd aspect of “Discolored Spots”: The method of the 22 nd aspect of “Discolored Spots”, wherein leaves of the plant illuminated by the first complementary light are screened for the dark areas for detecting a plant disease or inappropriate plant treatment causing yellow coloring of the leaves.
24 th aspect of “Discolored Spots”: The method of the 22 nd or 23 rd aspect of “Discolored Spots”, wherein the first complementary light is green light.
The first complementary color spectrum has a spectral intensity in the green spectral range only.
25 th aspect of “Discolored Spots”: The method of any of 18 th to 24 th aspects of “Discolored Spots”, wherein a first image of the plant illuminated by the first complementary light is captured and screened for dark and/or bright areas by digital image evaluation.
26 th aspect of “Discolored Spots”: The method of the 25 th aspect of “Discolored Spots”, wherein the number of dark areas in the first image is counted and/or the number of bright areas in the first image is counted.
Apart from a disease detection, the dark and/or bright area screening can for instance be used for evaluating the number of flowers or fruits (an approximate value), which can allow for a yield prediction (see the element “Yield Prediction” in detail).
27 th aspect of “Discolored Spots”: The method of any of the 18 th to 26 th aspects of “Discolored Spots”, wherein the plant is, subsequently to the illumination with the first complementary light, illuminated by a second complementary light with a second complementary color spectrum, which has a second spectral gap in comparison to a white light spectrum, the second spectral gap lying in another spectral region than the first spectral gap.
28 th aspect of “Discolored Spots”: The method of any of the 18 th to 26 th aspects of “Discolored Spots”, wherein the illumination unit illuminates the plants at different wavelengths (each wavelength range is emitted consecutively, i.e. only during separate time intervals), i.e. performs a spectral scan mode for probing discolored areas.
In other words, a spectral scan is performed, see the above remarks on the “spectral scan mode”. Further, subsequently to the illumination with the first/second complementary light, the plant can be illuminated by a third complementary light with a third complementary color spectrum, which has a third spectral gap in comparison to a white light spectrum, the third spectral gap lying in another spectral region than the first and the second spectral gap.
The complementary light source can be adjustable to emit the different complementary light spectra subsequently, or a plurality of complementary light sources can be provided.
29 th aspect of “Discolored Spots”: The method of the 27 th aspect of “Discolored Spots”, wherein a first image of the plant illuminated by the first complementary light is captured and a second image of the plant illuminated by the second complementary light is captured, wherein an image comparison of the first and the second image is performed.
30 th aspect of “Discolored Spots”: An agricultural system for a method according to any of the 18 th to 29 th aspects of “Discolored Spots”, the agricultural system comprising
a light fixture for emitting light, a growth area for growing a plant, a sensor device, an actuator device, a computing device, wherein the sensor device comprises an image capture device for capturing an image of the plant, and wherein the computing device is configured to process the image captured by the image capture device and, based on an outcome of the image processing, to trigger the actuator device and/or to output a signal to a user interface.
The actuator device can for instance perform a pest control or crop spraying, or a targeted fertilization. It can also unload the plant to a separate treatment location, see “Horticulture Processing Line” in detail.
The agricultural system can in particular be configured to illuminate the plant with the first complementary light. The image of the plant is captured when the plant is illuminated by the first complementary light.
31 st aspect of “Discolored Spots”: The agricultural system of the 29 th aspect of “Discolored Spots”, wherein the computing device is configured to screen the image captured by the image capture device for dark areas and/or for bright areas.
32 nd aspect of “Discolored Spots”: The agricultural system of the 29 th or 31 st aspect of “Discolored Spots”, wherein the computing device is configured to access a database, which comprises data on plant diseases and disease-related discolorations, wherein the image processing comprises a matching with the data comprised in the database.
33 rd aspect of “Discolored Spots”: The agricultural system of any of the 29 th to 32 nd aspects of “Discolored Spots”, wherein the complementary light source for emitting the first complementary light is comprised in the light fixture, the computing device being configured to switch between an investigation mode, in which the complementary light source emits the first complementary light, and an agricultural lighting mode, in which the complementary light source is switched off and another light source of the light fixture emits light to assist a growth of the plant.
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The light emitted by the other light source can for instance be defined in a light recipe.
34 rd aspect of “Discolored Spots”: The agricultural system of any of the 29 th to 33 rd aspects of “Discolored Spots”, comprising a light guide coupled to the complementary light source, wherein the light guide is provided for guiding the first complementary light to the plant.
The light guide can for instance be a fiber optic cable, see the element “Light Guides” in detail.
“Disease & Pest Control”
According to the element “Disease & Pest Control” of the disclosure, diseases and pests are identified based on collecting data about the plants and, optionally, about the ambient conditions in the target area as well. Then, a probability for the presence of a disease or the occurrence of pests is determined by comparing the collected data with reference data. Depending on the probability, and if need be, appropriate measures are proposed or introduced automatically.
1 st aspect of “Disease & Pest Control”: More specifically, the controlled agricultural system, comprises a sensor device for acquiring data in a target area, a computing device connected to the sensor device, a data storage device connected to the computing device, wherein the computing device is configured to compare the data of the sensor device with the data stored in the data storage device and detect deviations between the two sets of data, a control unit connected to the computing device, wherein the computing device is configured to output control commands to the control unit depending on the detected deviations, a light fixture connected to the control unit, wherein the control unit is configured to convert the control commands of the computing device into control signals for the light fixture.
The controlled agricultural system is configured to allow the identification of changes to plants that may be caused by diseases or pests, the identification of these diseases or infestation by pests and the introduction of measures, in particular countermeasures, which contain light recipes, in particular UV-A and UV-B radiation, but also radiation in the blue and yellow spectral range. This is because it is known that certain light recipes are harmful to pests, such as lice, arachnids, acari, and bacterial pathogens. To this end, the controlled agricultural system may comprise at least one light fixture (agricultural light fixture) with corresponding light sources. Furthermore, the countermeasures may contain light recipes, which reduce the plant stress (biotic stress). For reducing biotic stress, illumination parameters may be adapted, for example, the illumination duration and/or the illuminance may be changed, e.g. reduced, and/or the light spectrum of the illumination may be changed.
2 nd aspect of “Disease & Pest Control”: A controlled agricultural system, comprising a sensor device for acquiring data in a target area, a computing device connected to the sensor device, a data storage device connected to the computing device, wherein the computing device is configured to compare the data of the sensor device with the data stored in the data storage device and detect deviations between the two sets of data, an actuator device connected to the control unit, wherein the control unit is configured to convert the control commands of the computing device into control signals for the actuator device.
By way of example, measures may also comprise a change in the room temperature, the humidity, ventilation, the addition of nutrients, fertilizer, pesticides, pheromones, and the addition of medicine such as systemically acting pesticides to the nutrients. Further measures may contain a geometric modification of the light fixture position, the light fixture configuration and the light fixture emission characteristic. To this end, the controlled agricultural system may comprise corresponding actuators, which carry out these measures.
A further measure in the case of an infestation by pests may include traps being illuminated in such a way that insects are attracted thereby, said insects leaving the plants and being locked in the traps or adhering thereto (sticky traps). This can be assisted by pheromones, etc. Likewise, it is possible to attract predators for the pests, such as mesostigmata, which attack spider mites. To this end, the plants can be illuminated with light in the UV range (250-380 nm) and/or in the blue-green range (500-550 nm).
3 rd aspect of “Disease & Pest Control”: The controlled agricultural system according to the 1 st and 2 nd aspect of “Disease & Pest Control”.
Furthermore, it may be advantageous to combine the controlled agricultural system according to the 1 st aspect of “Disease & Pest Control” with the controlled agricultural system according to the 2 nd aspect of “Disease & Pest Control”.
4 th aspect of “Disease & Pest Control”: The controlled agricultural system according to any one of the 1 st to 3 rd aspect of “Disease & Pest Control”, wherein the sensor device is designed to acquire data of plants growing in the target area and/or data in relation to the ambient conditions in the target area.
Therefore, the controlled agricultural system is equipped with sensors, for example optical sensors, which identify the growth of the plants, the reflectivity of the leaves or the stress of the plants, for example. The growth of the plants may be detected by the density of the leaves, plant morphology, and leaf area index.
However, sensors may also identify the fluorescence radiation emitted by plants (after irradiation with excitation radiation). Chlorophyll fluorescence may be a particularly suitable option since the photosystem or the respiration changes in the case of disease or environmental conditions. Sensors may also measure a change in color of the plant (see e.g. the element “Discolored Spots Detection”), in particular of the leaves. Sensors may also determine gases released by plants or determine the concentration of said gases in the ground.
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Sensors may also identify the pests directly or typical damage to the plants, which indicates infestation by pests (stunted growth, deformations or other malformations). Here, use can be made of optical sensors such as cameras with image recognition, LiDAR systems for acquiring the plant morphology (see e.g. the element “LiDAR Plant Surveillance”), spectroscopic measurement appliances, which analyze spectral properties of the irradiation light, reflected from the infested plants, but also acoustic sensors which register characteristic noises from the pests.
Deviations that indicate a disease or negative change in the plant health or an infestation by pests are determined by the comparison with a characteristic growth behavior or characteristic physical or chemical properties. As already explained above, the type of disease or pest infestation can be determined by exact analysis of the leaf colors or plant forms, for example.
The comparison data are stored in a database and can be evaluated by an evaluation unit, in particular also in statistical fashion. The comparison with an intended value can be implemented by direct parameter comparison; however, artificial intelligence methods (such as deep learning) can also be used for the comparison of statistical evaluation. A parameter comparison can include an analysis and comparison of the plant morphology and a prediction, derived therefrom, for the further growth or the morphological embodiment of the plants. From the comparison of the measured data with the characteristic values (intended values), the system establishes a probability for the occurrence of the disease or the infestation by pests. Furthermore, such an evaluation unit can be provided to create predictions of a possible outbreak of disease and thereupon output a corresponding warning to the operator and/or customer of an agricultural system controlled in this fashion.
If the probability lies above a first threshold, then there probably is an affliction by disease or pests. The system informs the operator or planter, for example, about the discovery of the possible disease or infestation by pests and proposes a further analysis in order to determine the disease or the infestation by pests more accurately.
If the probability lies above a second threshold, the system can propose a specific countermeasure for the disease or the infestation by pests or (in a further embodiment) autonomously carry out the countermeasures described above in exemplary fashion.
In order to carry out the comparison of the sensor data with the comparison data (intended data), the controlled agricultural system comprises a computing device. Here, the sensor data and the comparison data are supplied to the computing device. Depending on the result of the comparison, the computing device, via a control unit, actuates the light sources in the respective light fixture or, optionally, the actuators as well.
Part of the controlled agricultural system, for example the computing device or the data storage device, may be local, but it may also be network-based or cloud-based.
Furthermore, according to the aspect “Disease & Pest Control”, a method for identifying and reacting to diseases and pests is proposed.
5 th aspect of “Disease & Pest Control”: More specifically, the method for agricultural management, according to “Disease & Pest Control”, comprises the steps of monitoring the plants in a target area by collecting data about the plants and/or the ambient conditions in the target area, comparing the collected data to corresponding intended data, determining whether deviations have occurred during the comparison, determining the probability for the occurrence of a disease or pest infestation on account of the determined deviations and if the probability lies under a first threshold then no further measures are introduced, if the probability lies between a first threshold and a second threshold then an information item that a disease or a pest infestation may be present is output and/or further analyses proposed, if the probability lies over a second threshold then countermeasures are propose or, alternatively, countermeasures are independently introduced.
The probability for the occurrence of a disease or pest infestation may be determined as follows. First, the difference values of the relevant parameters that deviate from the respective intended parameter values are calculated, i.e. in each case the absolute value of the measured value minus the intended value of a parameter. Relevant parameters in this context are parameters that indicate or influence the growth and/or health status of the plants, for example, the color of the plants, temperature and humidity of the environment, etc. Then each difference value is multiplied with a respective weighting factor, and the products are, finally, accumulated. The resulting sum is a measure of the probability. The respective weighting factors depend, amongst others, on the number of measured parameters. For instance, the partial probabilities have to be normalized to result in a total sum of the value 1 if the plants are actually infected by a specific disease. Furthermore, a weighting factor may be the smaller the less relevant the respective parameter is for determining a disease. Furthermore, the weighting factors may be modified with the help of learning algorithm (AI, deep learning) based on empirical data to improve the reliability of the detection of a disease or infection with pest.
6 th aspect of “Disease & Pest Control”: The method for agricultural management according to the 5 th aspect of “Disease & Pest Control” carried out using a controlled agricultural system according to any one of the 1 st to 4 th aspect of “Disease & Pest Control”.
7 th aspect of “Disease & Pest Control”: A machine-readable computer product, comprising a multiplicity of program instructions which, when executed on the computing device of the controllable agricultural system according to any one of the 1 st to 4 th aspect of “Disease & Pest Control”, cause the Controlled Agricultural System to execute the method for detecting and reacting to diseases or pests of plants according to the 6 th aspect of “Disease & Pest Control”.
›SUMMARY OF THE DISCLOSURE · 25 of 73
“Yield Prediction”
According to the element “Yield Prediction” of the disclosure, an automated yield forecast for flowering plants like tomatoes or strawberries is proposed. To this end, a controlled agricultural system is configured to be able to predict the yield of flowering plants growing in a target area (cultivated area).
1 st aspect of “Yield Prediction”: A controlled agricultural system, comprising a sensor device, comprising sensors able to detect flowers and/or buds of plants, a data storage device, wherein conversion rates of flower to fruit of plants are stored, a computing device, configured to identify and count the flowers/buds from the data of the sensor device, and further configured to predict the yield based on the number of the flowers/buds and the respective conversion rate retrieved from the data storage device.
2 nd aspect of “Yield Prediction”: Alternatively, a controlled agricultural system, comprises a sensor device, comprising sensors able to measure the biomass of plants, and further comprising sensors able to measure environmental parameters like light intensity, light spectrum, temperature, air movement, humidity, chemical composition of soil, air, fluids, a computing device, configured to predict the yield based on the biomass of the plants and current and/or future environmental data measured by means of the sensor device.
According to the alternative approach, the actual biomass is measured and current and/or future environmental data (temperature, humidity, light intensity, light spectrum . . . ) are in some embodiments/implementations included to estimate the yield. Biomass in this context refers to the mass of the plants, e.g. deduced from the number of plants and their size, i.e. the size of their stems and/or leaves.
3 rd aspect of “Yield Prediction”: The controlled agricultural system according to the 1 st or 2 nd aspect of “Yield Prediction”, further comprising a user interface configured to deliver the result of the prediction.
4 th aspect of “Yield Prediction”: The controlled agricultural system according to any one of the 1 st to 3 rd aspect of “Yield Prediction”, wherein the sensor device comprises one or more of the following sensors or a combination thereof: imaging system, e.g. still or video camera, in some embodiments/implementations TOF camera or stereo camera, LIDAR system, color sensor.
The controlled agricultural system comprises at least one sensor, which is able to detect the flowers (or buds) at a plant or to measure the biomass of the plants in the target area. For instance, the at least one sensor may comprise a camera and an image recognition system (object recognition and classification) to detect flowers (or buds) at a plant.
Furthermore, the controlled agricultural system comprises a computing device configured to identify the flowers (or buds) from the data measured by the at least one sensor. The computing device may host the image recognition system. It may use machine learning/deep learning algorithms to detect flowers. Alternatively or in combination, it may also detect the flowers directly based on the color of the flower (e.g. yellow for tomatoes) and/or the typical size derived from the picture, either as an absolute value or relative to the size of other parts of the plant (e.g. leaves).
5 th aspect of “Yield Prediction”: The controlled agricultural system according to any one of the 1 st to 4 th aspect of “Yield Prediction”, wherein the sensor device further comprises sensors able to measure the current status of growth/ripening of the plants/fruits.
6 th aspect of “Yield Prediction”: The controlled agricultural system according to the 5 th aspect of “Yield Prediction”, wherein typical time schedules of ripening of the fruits are stored in the data storage device, and wherein the computing device is configured to calculate a prediction for the harvesting time of the fruits based on the currently detected status of growth/ripening of the plants/fruits and the typical time left until ripeness of the fruits according to the time schedules.
To cover an extended cultivated area, multiple sensors, e.g. cameras, may be distributed within the area. For instance, the sensors/cameras may be attached fixedly in the greenhouse or at posts in the field. Some or all of the sensors (cameras) may be attached movably at a drone or robot and move through the greenhouse or the field, in some embodiments/implementations autonomously.
The number of flowers or buds per plants may be assessed individually for each plant in the cultivated area of the field or the greenhouse to obtain the overall number of flowers or buds in the cultivated area. If the number of plants is too large, a statistical approach can be chosen, i.e. limiting the measurements to a representative selection of plants (sub group). For instance, only every nth plant is measured, plants in a certain distance from the next plant are measured or plants in areas of the field that are known to be representative for the whole field (cultivated area) are measured. The number of flowers for the whole field (cultivated area) is then extrapolated from the measured number of flowers of this subgroup of plants.
Furthermore, according to “Yield Prediction”, a method for predicting the yield is proposed.
7 th aspect of “Yield Prediction”: More specifically, a method for agricultural management, comprises at least one controlled agricultural system and the steps of detecting the flowers or buds of the plants by means of the sensor device and the computing device assessing the number of flowers/buds by means of the computing device and based on the data measured by the sensor device predicting the yield by retrieving the respective conversion rate of the plant species from the data storage device and weighing the number of flowers assessed in the previous step with the conversion rate by means of the computing device.
8 th aspect of “Yield Prediction”: Alternatively, a method for agricultural management, comprises at least one controlled agricultural system and the steps of measuring the biomass of the plants by means of the sensor device and the computing device, measuring environmental parameters by means of the sensor device and the computing device, predicting the yield based on the biomass and the environmental data by means of the computing device.
›SUMMARY OF THE DISCLOSURE · 26 of 73
For predicting the yield, the method for agricultural management, according to the aspect “Yield Prediction”, uses a typical conversion rate from flowers to fruits available for each plant species in a database, which is stored in a data storage device of the computing device. The conversion rate is the rate at which flowers result in fruits. For instance, a conversion rate of 0.5 means that only half of the flowers eventually result in fruits (e.g. 10 flowers would result in 5 fruits). The typical conversion rate may be the average value of conversion rates observed in the past. The conversion rate may depend on additional parameters like the temperature, humidity, etc., which may be measured as well, in order to improve the accuracy of the prediction. For example, the pollination performance of the bumble-bees is different, depending on the species, temperature, air movement, day length, humidity, etc. It also depends on the amount of bumble-bees the grower is using. All these parameters have to be considered to derive a correct yield prediction. The calculated conversion rate can also take into consideration future changes in parameters like temperature, humidity or illumination. The parameters may be checked regularly. In case deviations are observed, the conversion rate and with it the predicted yield may be updated.
9 th aspect of “Yield Prediction”: The method for agricultural management according to 8 th aspect of “Yield Prediction”, further comprising the step of delivering the result of the prediction to the user (e.g. farmer or customer) by means of the user interface.
Using the typical conversion rate and the measured or extrapolated number for flowers in the cultivated area, the expected number of fruits is calculated by the computing device, taking into consideration that not all fruits will “survive” until harvesting, as they may drop, for example, due to low water, bad nutrition or something else. Using the average weight of the fruits, the expected total yield can be calculated, e.g. in kilograms.
10 th aspect of “Yield Prediction”: The method for agricultural management according to any one of the 7 th to 9 th aspect of “Yield Prediction”, further comprising the steps of detecting the current state of ripening of the plants/fruits by means of the sensor device and the computing device, predicting the harvesting time by retrieving the time schedule of ripening from the data storage device, comparing it with the current state of the ripening and calculating the typical time left until ripeness of the fruits, according to the time schedules and by means of the computing device, and/or predicting the next stage of ripening by retrieving the time schedule of ripening from the data storage device, comparing it with the current state of the ripening and calculating the typical time left for the next state of ripening, according to the time schedules and by means of the computing device.
Furthermore, the harvesting time may be forecasted as well. For this purpose, the system recognizes the state of the ripeness, e.g. the development of the flowers, the withering of the flowers, the creation of the fruits, and the different state of its ripeness. It can predict the expected harvesting time for each fruit based on average times stored in a database.
The prediction does not only include the final harvesting time but also the time when the next stage in the ripening process will be accomplished. The predicted time is compared regularly with the actual time. The forecast will be adjusted accordingly in case there should be a difference between actual and predicted time (e.g. a faster or slower ripening). In this case, the average ripening time stored in the database will be updated. The average ripening time for each stage (time schedule of ripening) is in some embodiments/implementations stored with corresponding environmental data like humidity, nutrition, illumination, temperature, and others.
The computing device may then present the calculated result (prediction) to a third party like the customer or farmer. The result may comprise a set of data, including the forecasted yield and, optionally, harvesting time, images (shot by still or video camera) or other graphical representation such as virtual or augmented reality of the plants.
11 th aspect of “Yield Prediction”: A computer program product, comprising a plurality of program instructions, which when executed by a computer system of an Controlled Agricultural System according to any one of the 1 st to 6 th aspect of “Yield Prediction”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 7 th to 10 th aspect of Yield Prediction”.
“Fungi Growth Inhibition”
According to the element “Fungi Growth Inhibition” of the disclosure, a controlled agricultural system with a light fixture is proposed that is configured to be able to illuminate plants during the nighttime to inhibit growth of fungi.
1 st aspect of “Fungi Growth Inhibition”: A Controlled Agricultural System for growing plants, comprising a lighting fixture for providing agricultural lighting, a fungi prevention light source for emitting light with a wavelength in a spectral range between 380 nm and 800 nm, wherein the Agricultural System is configured for applying the agricultural lighting to the plants during a day phase; and illuminating the plants with the fungi prevention light source at least temporarily during a night phase.
In addition to a lighting fixture for agricultural lighting, the agricultural system comprises a fungi prevention light source for emitting light with a wavelength in a spectral range between 380 nm and 800 nm. During a day phase, the agricultural lighting is applied to the plants. During a night phase, which usually is a dark period without any lighting at all, the plants are illuminated at least temporarily with the fungi prevention light source. In general, the duration of the additional illumination may vary from 1 minute to several hours, for instance 8 hours.
›SUMMARY OF THE DISCLOSURE · 27 of 73
Illuminating the plants during the night phase can inhibit or prevent the growth of pathogenic fungi that would cause plant diseases. For the purpose of illustration, reference is made to downy mildew below, even though the disclosure is not restricted to it. Downy mildew is one of the most occurring diseases in basil and can lead to huge losses in production up to a total loss of the crop.
By illuminating the plants during the night phase, the germination or sporulation of a fungi spore can be prevented or growth can be suppressed. Also sporulation can be slowed down, depending on temperature and light conditions. The fungi growth or germination/sporulation is affected by illumination, which means that a certain dark period duration is usually required to trigger the germination/sporulation of the spores. In simple words, it germinates and sporulates generally during the night. With the fungi prevention light source, the night or night phase is interrupted, preventing the germination. In other words, day conditions are simulated for the fungus during the night phase.
2 nd aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 1 st aspect of “Fungi Growth Inhibition”, wherein the wavelength of the light of the fungi prevention light source lies in a spectral range between 400 nm and 700 nm, in some embodiments/implementations between 600 nm and 700 nm.
On the other hand, the plants themselves require a certain dormant period, namely a night phase without agricultural lighting. Therefore, it is not beneficial, or can be even outright detrimental to illuminate the plants for 24 hours with the standard agricultural lighting. In some embodiments/implementations, the fungi prevention lighting has a reduced intensity and/or reduced spectral range. In a preferred embodiment, the wavelength of the fungi prevention light is at least 400 nm, particularly preferred at least 600 nm. An advantageous upper limit can for instance be 700 nm. Using red light is presumably advantageous in view the absorption behavior of the fungi.
Depending on the plants and fungi in detail, another advantage using red light can be a certain penetration through the leaves of the plants. In simple words, even by illuminating the plants from above, a certain treatment of the lower sides of the leaves as well as leaves at a lower position can be possible. In general, the fungi prevention lighting can be applied from any direction, from above, from the side, and/or from below. The light can be brought to any location of the plants by using for instance a light guide or optical fiber (see also “Light Guides”).
With this disclosure, the use of fungicides can be drastically reduced. In some countries, this option is even not available, as certain fungicides are not permitted for use. Treating fungus diseases with light furthermore allows to grow plants organically and reduces crop loss. The concept of using a night interrupting light treatment can be used for any plants, in particular for fungi infecting herbs, medical plants or ornamental plants.
3 rd aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 1 st or 2 nd aspect of “Fungi Growth Inhibition”, configured for illuminating the plants with the fungi prevention light source temporarily during the night phase, namely during at least one interval.
In a preferred embodiment, the plants are only illuminated temporarily during the night phase, namely during at least one interval. This can reduce a negative impact or influence on the plants themselves, which require the dormant period. The additional illumination may be provided once during the night (e.g. in the middle of the night) or at regular intervals (e.g. every hour) or randomly during the night. In some embodiments/implementations, the fungi prevention illumination is applied during a plurality of intervals during the night phase. Therein, the duration of the intervals themselves and/or the Off-time between the intervals can be constant or can vary. Any variation can be distributed regularly or randomly. Constant intervals are possible as well, the fungi prevention illumination might for instance be applied every 2 hours for one hour during night time.
4 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 3 rd aspect of “Fungi Growth Inhibition”, configured for illuminating the plants with the fungi prevention light source in a plurality of intervals during the night phase.
5 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 4 th aspect of “Fungi Growth Inhibition”, wherein an intensity of the illumination with the fungi prevention light source is varied, a different intensity being applied in different intervals.
In some embodiments/implementations, the fungi prevention light source is dimmable, for instance in the range of 3-100 μmol/(m 2 s). Likewise, the intensity of the fungi prevention illumination can be varied, so that a different intensity is applied in different intervals. A different intensity can be applied for each interval, or the intensity can vary in groups. Further, the intensity can also vary within an interval. In particular, the intensity may be higher in the intervals at the beginning of the night phase than at the end of the night phase, or it may be higher at the end of the night phase than at the beginning of the night phase. The maximum intensity may also be reached in the middle of the night phase.
6 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 5 th aspect of “Fungi Growth Inhibition”, configured for applying a dark period with no illumination at the beginning of the night phase.
7 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 6 th aspect of “Fungi Growth Inhibition”, wherein the duration of the dark period is at least 1 hour and not more than 4 hours.
›SUMMARY OF THE DISCLOSURE · 28 of 73
8 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 7 th aspect of “Fungi Growth Inhibition”, wherein the duration of the night phase is at least 2 hours and not more than 10 hours.
In a preferred embodiment, a dark period with no illumination is applied at the beginning of the night phase. In some embodiments/implementations, the duration of the first dark period is at least 1 hour and not more than 6 hours. In some embodiments/implementations, the duration of the night phase itself is at least 2 hours, further preferred at least 4 hours. Possible upper limits are 10 hours, in some embodiments/implementations 8 hours at maximum. Together, the day and the night phase add up to 24 hours.
9 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 8 th aspect of “Fungi Growth Inhibition”, wherein a total illumination time with the fungi prevention light source ( 200 ) during the night phase is not more than ⅔ of the duration of the night phase.
In a preferred embodiment, a total fungi prevention illumination time amounts to not more than ⅔ of the duration of the night phase. Possible lower limits can for instance be at least 1/100, 1/50, or 1/10 of the duration of the night phase. In case of an illumination in intervals, the total illumination time is obtained by summing up the duration of the intervals.
10 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 9 th aspect of “Fungi Growth Inhibition”, comprising a sensor device, the Controlled Agricultural System being configured for illuminating the plants with the fungi prevention light source depending on a measurement with the sensor device.
In a preferred embodiment, the fungi prevention illumination is applied based on a measurement performed with a sensor device. Infested plants can for instance be detected using a sensor like a camera or the like, for instance in combination with a picture recognition.
11 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st to the 10 th aspect of “Fungi Growth Inhibition”, comprising an additional fungi prevention UV light source for emitting UV light, wherein the Controlled Agricultural System is configured for illuminating the plants with the fungi prevention UV light source at least temporarily during the night phase.
In a preferred embodiment, an additional fungi prevention UV light source is provided. In some embodiments/implementations, the plants are illuminated with UV light at least temporarily during the night phase. The UV light can for instance be UV-A light (380-315 nm), UV-B light (280-315 nm) and/or UV-C light (200-280 nm).
12 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 11 th aspect of “Fungi Growth Inhibition”, and in combination with the 4 th or 5 th aspect of “Fungi Growth Inhibition”, wherein the plants are not illuminated by the fungi prevention UV light source in-between the intervals during the night phase.
13 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to the 11 th or 12 th aspect of “Fungi Growth Inhibition”, wherein the plants are not illuminated by the fungi prevention UV light source in at least one of the intervals.
In some embodiments/implementations, the plants are not illuminated with the UV light source between two intervals, in which the fungi prevention illumination is applied (e.g. red light). Particularly preferred, no illumination at all is applied between the intervals of the fungi prevention/UV illumination.
The fungi prevention illumination (in particular red light) during the night phase has the goal to disturb the growth cycle of the fungus, preventing it from growing and spreading. The additional UV illumination may even destroy already existing fungi.
If several illumination intervals are planned during the night phase, at least one of them might also include UV only. The fungi prevention time which uses UV-C-light may have a duration of 15 seconds to 1 minutes, whereas illumination with UV-A-light may last from 5 minutes to 5 hours to inactivate spores. UV-light could also be applied simultaneously with the red light. In some embodiments/implementations, the total duration of the fungi prevention illumination is longer than the duration of the UV illumination.
In some embodiments/implementations, the fungi prevention light source and/or the additional UV light source are integrated into the lighting fixture for the agricultural lighting. In general, the light source(s) can be controlled by a control unit, which controls for instance the intensity, the illumination duration of the light, and the dark periods between the illuminations. The intensities and durations can be controlled independently for the fungi prevention and the UV light source.
14 th aspect of “Fungi Growth Inhibition”: The Controlled Agricultural System according to any one of the 1 st or 13 th aspect of “Fungi Growth Inhibition”, configured for varying an additional environmental parameter during the night phase, in some embodiments/implementations at least one of temperature and humidity.
In a preferred embodiment, an additional environmental parameter is varied during the night phase, in some embodiments/implementations temperature and/or humidity. The risk of infestation of the plants by fungi is usually reduced by reducing the population density, using a dry cultivation (i.e. irrigation from below and possibly in the morning or only a few larger water sprayings), introducing a time interval to a subsequent crop cycle, preventing dew formation in the greenhouse (emergency dry heating, use of fans), using hygienic measures, or supplying balanced nutrients (e.g. avoiding nitrogen stress). If the fungus has infested the plants, the infested plants are usually removed immediately or treated with fungicides (if available).
›SUMMARY OF THE DISCLOSURE · 29 of 73
15 th aspect of “Fungi Growth Inhibition”: A Method for Controlling an Agricultural System according to any one of the 1 st to 14 th aspect of “Fungi Growth Inhibition”, comprising the steps of applying agricultural lighting to the plants during a day phase; and illuminating the plants with the fungi prevention light source ( 200 ) at least temporarily during a night phase.
Regarding further possible embodiments, reference is made to the description above and also to the aspect relating to the system of “Fungi Growth Inhibition”.
It is also possible to adjust the nightly irradiation composition (spectrum (blue, red, green, UV, IR), intensity) and cycles (can be different for different light spectral/colors) for plants into which a symbiotic fungus has been implanted (e.g. to produce chanoclavine in the plant).
16 th aspect of “Fungi Growth Inhibition”: Computer program product, comprising a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 14 th aspect of “Fungi Growth Inhibition”, cause the Controlled Agricultural System to execute the Method for Controlling a Controlled Agricultural System according to the 15 th aspect of “Fungi Growth Inhibition”.
The light treatment will be triggered by a control unit. The command for the control unit can be given by a computing device which either receives the command from the grower, or which triggers the treatment automatically based on the detection of the fungi by a sensor device. However, the treatment can also be initiated prophylactically to avoid the growth of fungi on the plants (e.g. every night, once a week or once a month). The respective illumination durations, dark periods and illumination intensities are stored in a database connected to or integrated into the computing device. The treatment method described here might be part of the overall control program of the light source.
“Sensor Retrofit”
According to the element “Sensor Retrofit” of the disclosure, a moveable irrigation device is equipped with a sensor device for measuring plant parameters, particularly parameters indicating health and growth stage of the plants.
1 st aspect of “Sensor Retrofit”: An Agricultural System, comprising a growth area for growing plants, an irrigation device for irrigating plants grown on the growth area and a sensor device, wherein the irrigation device is mounted moveable with respect to the growth area, and wherein the sensor device is mounted at the irrigation device and moveable with respect to the growth area, thus.
The Agricultural System according to “Sensor Retrofit” comprises an irrigation device moveable with respect to a growth area (or cultivated area) and a sensor device mounted at the irrigation device. When the irrigation device is moved over the growth area for irrigating the plants grown there, the sensor device is moved along with the irrigation device. Therefore, plants grown at different locations or regions of the growth area can be measured with the same sensor device.
Furthermore, most Agricultural Systems are equipped with an irrigation device anyway. Thus, the movement unit, which moves the nozzles over the growth area, is available already. The sensor device can be attached or retrofitted to this existing setup, which can be advantageous from an economical point of view as well. The “irrigation device” may not only be used for watering purposes but also for a treatment with fertilizers/pesticides or the like.
2 nd aspect of “Sensor Retrofit”: The Agricultural System according to the 1 st aspect of “Sensor Retrofit”, wherein the sensor device is an optical sensor, in particular a camera.
Many greenhouse growers are using an automated trolley as irrigation device. The trolley usually includes a bar or rail or arrangement of levers, which contains nozzles for irrigation or spraying of fertilizers/pesticides. The sensor device can for instance be a camera mounted to such a trolley, taking pictures of the plant surface while the trolley is turning back and forth over growth area, or other optical devices like a LiDAR (light detection and ranging) Time-of-Flight measuring and sensor device (see also “LiDAR Plant Surveillance”, below). These pictures can help the grower to find regularities and irregularities in the plant population (growth, morphology, fruition, health condition). The irrigation device can also be an irrigation robot, which can be used indoors or outside in open fields or vineyards, or a vehicle driving autonomously.
3 rd aspect of “Sensor Retrofit”: The Agricultural System according to the 1 st or 2 nd aspect of “Sensor Retrofit”, which is an indoor farm, the irrigation device being mounted below a ceiling above the growth area.
Plant growth can be influenced by several parameters like light intensity (photon flux), light spectrum, nutrients or temperature. Especially when experimenting with new settings of those parameters, a fast feedback about the plant growth, i.e. the morphological parameters, is necessary. Plant growth can mean the height of the plant, the size and number and orientation of the leaves, the diameter of the plant, the plant morphology, etc.
However, even when the parameters to grow plants in an agriculture system are set, a regular control if the plants are growing as expected is necessary, as undetected changes in the parameters, diseases or pests can affect the plant growth. It would also be beneficial to track plant growth data or growth indicators continuously, by day and night, and correlate the data to other external parameters like temperature, nutrients, photon flux, applied spectra, illumination ON and OFF cycles, etc.
4 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 3 rd aspect of “Sensor Retrofit”, wherein the irrigation device comprises a horizontal rail with a plurality of nozzles provided along the rail.
Usually, an irrigation device or trolley is made of metal profiles, in particular aluminum profiles. In a preferred embodiment of an in-house farm, the irrigation device is mounted below a ceiling above the growth area. It can for instance hang on a rod from the roof top. The sensor can be mounted to the irrigation device with clips or clamps (by a form-fit or with screws or the like). In some embodiments/implementations, the irrigation device comprises a horizontal rail with a plurality of nozzles provided along the rail.
›SUMMARY OF THE DISCLOSURE · 30 of 73
In a preferred embodiment, the sensor device is an optical sensor, in particular a camera. In general, other sensors are possible, for example temperature sensors (creating for instance a heat map) or ultrasound or LiDAR sensors to measure distances.
5 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 4 th aspect of “Sensor Retrofit”, comprising a plurality of sensor devices mounted removably to the irrigation device.
6 th aspect of “Sensor Retrofit”: The Agricultural System according to the 5 th aspect of “Sensor Retrofit”, wherein a distance between neighboring sensor devices amounts to 0.1 m at minimum and 1 m at maximum.
In a preferred embodiment, a plurality of sensor devices are mounted at the irrigation device. A distance between neighboring sensor along the trolley bar devices can for instance be at least 0.1 m and in some embodiments/implementations not more than 1 m. In detail, the spacing between the sensor devices or cameras will for instance depend on the mounting height and the angle of the lens of the camera.
7 th aspect of “Sensor Retrofit”: The Agricultural System according to the 5 th or 6 th aspect of “Sensor Retrofit”, wherein at least one sensor device differs from another sensor device in the parameter measured respectively.
8 th aspect of “Sensor Retrofit”: The Agricultural System according to the 7 th aspect of “Sensor Retrofit”, wherein the sensor devices, which differ in the parameter measured, are cameras with a different spectral sensitivity.
In some embodiments/implementations, at least some of the sensor devices differ in the parameter measured respectively, for instance cameras in their spectral sensitivity. The cameras can be equipped with same or different lens systems in order to cover various field-of-view settings and therefore different sensed or surveilled plant areas. The lens systems can be adjustable, in some embodiments/implementations by remote control. The cameras can be equipped for daylight picture taking and/or for nighttime picture taking using infrared-sensitive sensors. They can also be equipped with an UV-protective cover that is transparent for visual and/or infrared radiation. The cameras can also be equipped with cleaning devices or with removable optically transparent protective covers that can be cleaned, refurbished and so on.
In general, simple RGB cameras can be provided to create a general overview of the entire plant canopy. However, also multispectral or hyperspectral cameras can be used to measure e.g. the chlorophyll fluorescence or the fertilization status. With each passing of the irrigation device, pictures can be taken in different wavelength ranges, e.g. in the IR, visible range (whole spectrum or monochromatic) or UV. It is also possible that neighboring cameras take pictures at different wavelengths during one passing, e.g. the 1st, 4th, 7th, . . . camera takes pictures in the visible range, the 2nd, 5th, 8th, . . . camera takes pictures in the IR and the 3rd, 6th, 9th, . . . camera takes pictures at a certain wavelength (monochromatic). Pictures can be taken at regular time intervals or as a function of trolley speed that can for example be in the range between 5 and 25 km/h. Of course, a camera can also take videos for continuous surveillance and plant tracking.
9 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 5 th to 8 th aspect of “Sensor Retrofit”, wherein the sensor devices are provided along a rail.
10 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 4 th to 9 th aspect of “Sensor Retrofit”, wherein the rail with the sensor devices is mounted at the horizontal rail with the nozzles, the rails extending basically in parallel to each other.
In a preferred embodiment, the sensor devices are provided along a rail. This inventive rail equipped with the sensor devices/cameras, can be mounted to the existing structure (e.g. in parallel to the existing rail with nozzles) in different ways. For example, depending on the system, simple clips or clamps can be used. If necessary, a crossbar (or a steel rope) can be used to stabilize the structure.
11 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 5 th to 10 th aspect of “Sensor Retrofit”, comprising a computing device configured for collecting and merging the parameters measured by the sensor devices, a parameter map of the growth area being generated by merging the parameters.
A preferred Agricultural System comprises a computing device configured for collecting and in some embodiments/implementations merging the parameters measured by the sensor devices. Likewise, a parameter map of the growth area can be generated.
12 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 11 th aspect of “Sensor Retrofit”, configured for measuring a respective position of the irrigation device with respect to the growth area.
13 th aspect of “Sensor Retrofit”: The Agricultural System according to the 11 th and 12 th aspect of “Sensor Retrofit”, wherein the computing device is configured for generating a 2-D or 3-D model from the position information and the parameters measured by sensor device.
In general, each of the sensor devices/cameras can be controlled individually. With this setup it is possible to create a general overview of the entire surface, which can be analyzed by a software. In addition, a 3-D picture can be generated by evaluating or merging pictures from two or more cameras next to each other. Due to the different angles, a simple 3-D model of the surface can be calculated.
By calculating a 3-D model of the plants, data can be collected about:
i. Height ii. Shape iii. Angle of leaves
On the other hand, by calculating a 2-D model, data can be collected about:
i. Coloration, which also can be down-calculated to necrosis, virus or fungi disease ii. Malformation of leaves iii. Number of flowers iv. Missing plants v. Plant size vi. Plant height vii. Plant diameter viii. Nutrition status of the plants ix. Disease detection x. Water content
›SUMMARY OF THE DISCLOSURE · 31 of 73
In some embodiments/implementations, the position of the trolley will be measured to provide coordinates for the measured values, in particular for the pictures taken. The calculation of the position can be done using an (indoor) positioning system e.g. based on Bluetooth beacons, or knowing a start-point of the trolley and calculating the actual position based on the speed of the trolley and the time passed and/or using marks (like an QR-code) along the rail for positional checking and information input.
The measured parameters, in particular the picture data, will be sent to a general control unit. The data transfer can be wire-based (LAN, 5-core cable, or other existing cables for data transfer) or wire-less. The data can be transferred to the computing device via a control box or control unit. The latter can be equipped with a Wi-Fi module, which transfers the data to the computing device. A wire-based connection to the computing device is possible as well. The computing device can be linked to or comprise a climate control computer.
The computing device can be local (edge computing) or in the cloud. The data will be processed and alerts, growth status, etc. can be provided for instance on a dashboard to the grower. In case of deviation from the predicted or expected growth, an alert will be given. The alert can contain the kind of abnormality and where the abnormality was detected, for example with positional coordinates.
Data distribution and analysis can be performed using Artificial Intelligence and Deep Learning methods. Data distribution, analysis and data handling can use a blockchain technology in order to generate a tamper-proof distributed ledger-system. It is also possible to provide a low-resolution picture, with the software marking the area in a specific color where something is out of a normal behavioral condition or biological setting. Depending on the intelligence of the system, it can also give a recommendation to the user how to treat the plants.
14 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 13 th aspect of “Sensor Retrofit”, configured for moving the irrigation device forth and back over the growth area, wherein a measurement with the sensor device is only performed during one pass of the irrigation device.
15 th aspect of “Sensor Retrofit”: The Agricultural System according to the 14 th aspect of “Sensor Retrofit”, wherein the irrigation device is moved forth in a first pass and back in a second pass, and wherein the sensor device is moved ahead the irrigation device during the first pass and the measurement is performed during the first pass.
In a preferred embodiment, the irrigation device is moved forth and back over the growth area. Therein, a measurement with the sensor device is only performed during one pass of the irrigation device, either during a first pass forth or during a second pass back. In some embodiments/implementations, the measurement (picture taking) is done when the sensor device(s) is/are moving in front of the rail with the nozzles. The trolley is usually moving twice across the field (back and forth), i.e. the data can be collected either only during one pass of the trolley, or during both passages.
16 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 15 th aspect of “Sensor Retrofit”, comprising a light source mounted at the irrigation device and being moveable with respect to the growth area, thus.
In a preferred embodiment, a light source is mounted at the irrigation device. This can for instance be a high-power UV LED for disinfection or a red/far-red source for night interruption. In some embodiments/implementations, the light source is mounted to the rail as well. Along the rail, a plurality of sensor devices can be provided. For instance, each camera can be equipped with a respective light source. The light sources can emit light at the wavelength measured by the respective camera to improve the brilliance. They can also emit light with a complementary color of an expected disease reflectance as described in DE102018214676. Furthermore, the light sources can also emit infrared light for nighttime inspection with infrared-sensitive cameras.
17 th aspect of “Sensor Retrofit”: The Agricultural System according to any one of the 1 st to 16 th aspect of “Sensor Retrofit”, wherein the irrigation device and the sensor device share a common power supply.
In a preferred embodiment, the irrigation device and the sensor device share a common power supply. Alternatively, the power supply of the sensor device can be realized via a small solar panel with a battery on the top of the sleigh if no power supply is available. In some embodiments/implementations, the common power supply is implemented based on the existing infrastructure with an electric control box above each irrigation trolley. The power supply lines can go next to the irrigation pipes.
18 th aspect of “Sensor Retrofit”: A Method for Controlling an Agricultural System according to any one of the 1 st to 17 th aspect of “Sensor Retrofit”, wherein the irrigation device and the sensor device are moved over the growth area, and a parameter is measured by the sensor device.
For instance, morphological or other parameters measured can be analyzed by the computing device. The parameters and the result of the analysis can be provided to the farmer or a customer. In case of deviations, the system can automatically change a growth parameter (e.g. illumination or temperature) or it can inform the farmer or a customer (e.g. on a display about for instance the actual growth, simulated growth, growth prognosis, AR (augmented reality) or VR (virtual reality) representation, 2D and 3D plant configuration, and so on).
19 th aspect of “Sensor Retrofit”: A Computer program product, comprising a plurality of program instructions, which when executed by a computing device of an Agricultural System according to any one of the 1 st to 17 th aspect of “Sensor Retrofit”, cause the Agricultural System to execute the Method for Controlling according to the 18 th aspect of “Sensor Retrofit”.
›SUMMARY OF THE DISCLOSURE · 32 of 73
“LiDAR Plant Surveillance”
According to the element “LiDAR Plant Surveillance” of the disclosure, the growth of plants is monitored by measuring the decreasing distance between a distance-measuring device and the growing plants.
1 st aspect of “LiDAR Plant Surveillance”: More specifically, a controlled agricultural system, comprises a growth area for growing plants and a distance measuring device for measuring a distance to an object in a detection field, the distance measuring device being arranged in a relative position to the growth area such that the detection field and the growth area have at least an overlap.
The distance measuring device is oriented towards the growth area of the agricultural system, for measuring the distance to the plants grown there. For instance, it can be arranged above the growth area, “looking” downward onto the latter. Then, the distance measured will decrease the larger the plants become. In particular, the distance measurement can enable a profile measurement giving information on morphological parameters of the plants.
2 nd aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 1 st aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for a time-of-flight distance measurement.
In a preferred embodiment, the distance measurement is a time-of-flight distance measurement. In general, an ultrasonic measurement is possible, even though a light-based measurement is preferred, in particular with a LiDAR system. Therein, the term “light” is not restricted to the visible part of the electromagnetic spectrum, it also relates to UV and IR light, the latter can even be preferred.
3 rd aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 1 st or 2 nd aspect of “LiDAR Plant Surveillance”, the distance measuring device comprising a light source for emitting light pulses, in some embodiments/implementations laser pulses, and a sensor device for detecting echo pulses returning from the detection field after a reflection at the object.
A light source is provided for emitting the light pulses, in particular a laser source, which in some embodiments/implementations comprise one or more laser diodes. The light/laser pulses are emitted into the detection field and are reflected at the surface of the object(s) located there, for instance at the leaves in case of the plants. The measuring device further comprises a sensor for detecting the reflected pulses returning from the detection field, namely for detecting the echo pulses. From the time delay between the emission of the pulse and the detection of the echo pulse, namely from the time of flight δt, the distance can be calculated (d=δt·c/2).
In the following some further characteristics of a preferred LiDAR system are summarized:
The light source, in particular a laser, emits short light pulses (typically with a pulse half-width between 0.1 ns and 100 ns, here preferred between 0.1 and 10 ns). The sensor, which can also be sensor array, can for instance be a Photo-Diode, an Avalanche Photo Diode (APD), a Single Photon Avalanche Diode (SPAD), a PIN-Diode, or a Photo-Multiplier, it detects the echo pulse. In some embodiments/implementations, infrared light is used (wave length between 850 nm and 1600 nm, or larger), but visible or UV-light can be used as well. The light source can emit the light pulses with repeat frequencies between 1 kHz and 1 MHz, in some embodiments/implementations between 1 kHz and 100 kHz (this gives a pulse enough time to return back to the sensor; 2 μs delay time corresponds to a distance of 300 m, 1 μs to 150 m, and 100 ns to 15 m). The light can be pulsed stochastically to filter out the background illumination, which could be sunlight but also heat radiation. This will improve the signal-to-noise ratio of the signal.
4 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 3 rd aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for a spatially resolved distance measurement.
In some embodiments/implementations, the distance measuring device is adapted for a spatially resolved distance measurement (referred to as “enhanced” system below). The detection field is segmented into a plurality of segments, for each segment a distance value is measured. This gives a distance image with a spatial resolution, namely a three-dimensional picture of the environment, in particular of the growth field.
5 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 4 th aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for assigning the echo pulses received with the sensor device to different solid angles of the detection field.
6 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 4 th or 5 th aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for emitting the light pulses into different solid angles of the detection field.
7 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 4 th to 6 th aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for adapting the size of the detection field to the growth area and/or a growth state of the plants.
On the one hand, the spatial resolution can be achieved with the sensor device. Therein, the sensor assigns the echo pulses returning from the detection field to different solid angles. The sensor or sensor array comprises several pixels, each detecting the reflected light in a certain solid angle. This can for instance be achieved with CCD or CMOS sensor combined with an optical system, for instance a lens. The optical system guides the echo pulses from the different solid angles onto different pixels, for instance different areas of the CCD or CMOS array. Likewise, each pixel is linked to a respective solid angle, and the echo pulse can be assigned accordingly. In such a setup, the light/laser source can for instance illuminate the whole detection field (area of interest) in a flash mode.
›SUMMARY OF THE DISCLOSURE · 33 of 73
On the other hand, the spatial resolution can also be achieved by scanning the light/laser pulses across the detection field, for instance by moving mirrors like MEMS-mirrors. Accordingly, at a certain point in time, the light/laser pulse is emitted in a certain solid angle (depending on the current tilt of the mirror). Thereafter, the next pulse is emitted in another solid angle, and so on. In this setup, the sensor can even consist of just one sensor element with an optic which covers the whole detection field (the sensor has no spatial resolution). However, as the pulse is emitted in a certain solid angle, the measuring device (or control/computing device connected thereto) knows from which solid angle the detected echo pulse returned.
It is also possible to combine a sensor with a spatial resolution and the scanning emission in a hybrid approach.
8 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 4 th to 7 th aspect of “LiDAR Plant Surveillance”, the distance measuring device being adapted for a spectrally resolved distance measurement, namely for emitting and detecting light pulses having a different wavelength.
In some embodiments/implementations, the distance measuring device is adapted for a spectrally resolved distance measurement, namely for emitting and detecting light pulses having a different wavelength (referred to as “enhanced” system below). An enhanced system can employ various wavelengths at the same time, then a (segmented or multi-) sensor needs to have respective filters, or apply the filters sequentially. Each wavelength could also use another pulse-pattern, so that it can be differentiated from other wavelengths. Using different wavelengths can provide additional information, like leaf reflectivity, fluorescence radiation, e.g. chlorophyll fluorescence. In the latter case, any subsequent pulse needs to wait until a typical fluorescence or phosphorescence decay time is over. Using light pulses having different infrared wavelengths will help increase the Signal-to-Noise Ratio (SNR) or the measured Lidar Pulses, since more measurement data can be used for data measurement and processing, object recognition and classification.
It is also possible to use laser radiation in the visible or ultraviolet wavelength range for the described scanning application. Therefore, the term LIDAR includes laser radiation in the entire wavelength range from Ultraviolet to Infrared.
Using visible laser radiation in the visible wavelength range can be used to detect and measure not just plant morphology but also biological or chemical plant features and health conditions.
Early disease detection for plants is important, especially in a closed environment like a vertical farm, where diseases can spread easily. Different kinds of diseases or stress can cause different symptoms at a plant, for example on plant leaves, petals, stem or roots. Some can lead to a reduced growth of the plant, others, like the Tobacco mosaic virus, which can infect tobacco, pepper, tomato and cucumber, mainly cause “mosaic”-like mottling and discoloration on the leaves. Causes of discolorations, depending on plant type, can for example be caused by lack of nutrients or lack of chemical elements like Nitrogen (N), Phosphor (P), Potassium (K), Sulfur (S), Manganese (Mn), over-supply of nutrients, too much light, too rapid temperature changes, lack of air circulation, too dry air, too much irrigation, bacterial and virus infestation causing for example bacterial blight and bacterial wilt, soil contamination, soil temperature and many others. In addition to discoloration effects, plant leaves can develop holes.
It is known to use cameras to observe plants and detect color changes that could be associated with diseases, i.e. the discolored parts have changed from their naturally provided colors (according to their actual growth stage) to a changed color impression, therefore they have become discolored. Discolorations can affect only parts or small segments of a plant body (stem, petals, leaves) or greater areas. However, some of these color changes, particularly in an early stage of a disease, only affect small parts of the leaves, or the contrast between the discolored part and the normal colored part is small, thus making it easy to overlook the discolored areas. The aspect “Plant Surveillance” targets to intensify the contrast between discolored and normal colored parts of a plant.
Furthermore, some color changes (discoloration) signal a next stage of ripening, e.g. the change of color in fruits. For instance, tomatoes discolor from green to red while ripening, eventually triggering harvesting.
It is therefore possible to use such a LIDAR scanning system (as described above) in a Controlled Agricultural System for plant breeding and cultivating, particularly for detection of plant diseases and various stages of ripening, comprising by using a data storage device comprising data, which are related to spectra of light, particularly of light with colors complementary to colors of parts of plants (Complementary Color Spectrum CCS), for example, complementary to discolored areas or parts of plants, an LIDAR illumination device able to emit light with a color spectrum according to the data stored in the data storage device and illuminate plants, a sensor device able to detect the light reflected by the illuminated plants, a computing device configured to control the illumination device based on the data of the database, and further configured to analyze the data from the sensor device and detect dark areas on the plants.
9 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 1 st to 8 th aspects of “LiDAR Plant Surveillance”, wherein the distance measuring device ( 200 ) is arranged in a distance from the growth area of 30 m at maximum.
In a preferred embodiment, the distance measuring device is arranged in a distance of 30 m maximum from the growth area, in some embodiments/implementations 25 m, 20 m, 15 m or 10 m at maximum (possible lower limits are for instance at least 2 m, 4 m or 5 m). A LiDAR system can reach a resolution of a few millimeters at a distance of about 10 meters. This resolution is sufficient to detect morphological parameters of plants like biomass, size, leave size, flowers (number and size), etc., future systems will even provide a better resolution.
›SUMMARY OF THE DISCLOSURE · 34 of 73
10 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 1 st to 9 th aspects of “LiDAR Plant Surveillance”, which is an indoor farm, the distance measuring device being mounted below a ceiling above the growth area.
11 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 1 st to 10 th aspects of “LiDAR Plant Surveillance”, comprising a light fixture for illuminating at least a part of the growth area, wherein the distance measuring device is a part of the light fixture.
In a preferred embodiment, the Controlled Agricultural System is an indoor farm, for instance a greenhouse or vertical farm. To detect morphological (and other) parameters, the LiDAR-system (or enhanced-LiDAR system with spectral/spatial resolution) can be attached at an elevated place in the greenhouse or vertical farm, it can be mounted below a ceiling above the growth area, either at the ceiling itself or at a scaffold. The LiDAR-system can also be integrated into a light fixture which is provides artificial lighting to the growth area; the LiDAR-system can for instance be arranged in the housing of the light fixture.
In a simple approach, one (enhanced) LiDAR-system attached in the center of the greenhouse could be sufficient to get a rough overview. However, installations in the greenhouse like lighting fixtures might block the laser pulses and the (enhanced) LiDAR system will only measure a plant from one direction.
In general, the distance measuring device (LiDAR-system) can be mounted movably for capturing the growth area from different sides. It can for instance move along a track in a vertical farm. In a vertical farm, the plants grow on shelfs in racks, the LiDAR-system could then move along the rack to measure the plants on each shelf.
12 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 1 st to 11 th aspects of “LiDAR Plant Surveillance”, the distance measuring device being immovably mounted in its relative position with respect to the growth area.
In some embodiments/implementations, the distance measuring device (LiDAR-system) is mounted immovably (in an immobile manner) with respect to the growth area. In comparison to the prior art mentioned above, this mounting is far less complex. With a LiDAR-system, the light can be flashed or scanned over the entire detection field/growth area, whereas in the prior art the whole sensor system has to be moved across the growth area. A LiDAR-system does not need a movable, mechanical support and can continuously measure a much wider area.
13 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to any one of the 1 st to 12 th aspects of “LiDAR Plant Surveillance”, comprising an additional distance measuring device for measuring a distance to an object in a detection field, in some embodiments/implementations by a light pulse time-of-flight distance measurement, the distance measuring devices being arranged to capture different regions of the growth area and/or to capture the growth area from different points of view.
In a preferred embodiment, the Controlled Agricultural System comprises an additional distance measuring device for measuring a distance to an object in a detection field, in some embodiments/implementations an additional LiDAR-system. The LiDAR-systems are arranged to capture different regions of the growth area and/or to capture the growth area from different points of view. Using several LiDAR-systems in a vertical farm or greenhouse can enable the creation of a full view of the plants. In a simple approach, an (enhanced) LiDAR-system is attached close to one of the four corners of a greenhouse. From this perspective, the whole area of interest can be covered. If the line of sight of one (enhanced) LiDAR is constrained, an (enhanced) LiDAR from another angle can cover this area. In addition, the plants can be measured from all angles, creating a 360°-view of the plant morphology.
When a plurality of LiDAR-systems are provided, each can scan the whole growth area (e.g. the full view the system is able to scan). The detection field can even be larger than the growth area. A computing device, either a local or a central device, can distinguish the growth area from other parts of the greenhouse/farm (e.g. walls). The computing device can then reduce or adapt the scanned area for each LiDAR-system so that it only covers the area of interest (“commissioning”).
In a preferred embodiment, the Controlled Agricultural System is configured for a time-synchronized measurement with the different distance measuring devices/LiDAR-systems. The control unit or computing device of the Agricultural system activates the LiDAR-systems at a specific point in time or at specific points in time—for example during illumination with light emitted by the regular horticulture lighting fixtures with a specific color, or with a specific spectral intensity or other photometric values, like photosynthetically active radiation (PAR) or Photon Flux, or only during a dark time period (no lighting), or after the plants have been treated with UV-radiation—in the greenhouse or horticultural indoor farm in an interleaved mode (i.e. one after the other) to avoid that one LiDAR-system interferes with a second LiDAR-system, leading to a “false” signal.
14 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 13 th aspects of “LiDAR Plant Surveillance”, wherein the additional distance measuring device is adapted for emitting and detecting light pulses having another wavelength than the light pulses emitted and detected by the first distance measuring device.
In a preferred embodiment, the distance measuring devices/LiDAR-systems are equipped for operating in different spectral regions. Each sensor (IR, UV, visible) is connected to a computing device (via its control unit). Since different wavelengths are used, the signals from another (wrong) LiDAR light source can be ignored by the sensor (e.g. by using a wavelength-filter).
›SUMMARY OF THE DISCLOSURE · 35 of 73
15 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 13 th or 14 th aspect of “LiDAR Plant Surveillance”, being configured for a clocked and/or time-synchronized measurement with the distance measuring devices, one after the other.
In a preferred embodiment, the Controlled Agricultural System is configured for a clocked measurement with the different distance measuring devices/LiDAR-systems. The control unit or computing device of the Agricultural system activates the LiDAR-systems in the greenhouse in an interleaved mode (i.e. one after the other) to avoid that one LiDAR-system interferes with a second LiDAR-system, leading to a “false” signal.
16 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 13 th to 15 th aspect of “LiDAR Plant Surveillance”, comprising a computing device configured for merging distance images taken by the distance measuring devices.
17 th aspect of “LiDAR Plant Surveillance”: The controlled agricultural system according to the 16 th aspect of “LiDAR Plant Surveillance”, comprising a reference point in a defined relative position with respect to the growth area, the computing device being configured for merging the distance images by means of the reference point.
Each LiDAR-system will provide a three-dimensional set of (time-sequential) pictures, from its point of view. Different wavelength ranges are possible, but not mandatory. To create a three-dimensional picture of each plant, the pictures of the LiDAR-systems need to be mapped over each other. To map them, the system in some embodiments/implementations uses a reference point. This reference point can be an object in the greenhouse and the respective distances are calculated from this object. Alternatively, the reference point can be the walls of the greenhouse. The computing device receives the information from the LiDAR-system how far a plant is away from the opposite wall, and it knows the distance between the walls of the greenhouse.
The height of a plant is measured with respect to the upper surface of the soil. Usually, the plants do not cover the whole soil, so that this information should be available any time. However, the system can make a reference measurement before the first plant is planted, so that the correct height of the plant can be calculated even if the plants cover the soil completely.
The detected morphological parameters will be analyzed by the computing device. The parameters and the result of the analysis can be provided to the farmer or a customer. In case of deviations, the system can automatically change a growth parameter (e.g. illumination or temperature) or it can inform the farmer or a customer (e.g. on a display about for instance about the actual growth, simulated growth, growth prognosis, yield forecast, AR or AV representation, and so on). Such a system is able to measure even at night as to detect night behavior (e.g. also after a nightly UV-exposure).
It is also possible for a LiDAR system to recognize other objects inside a greenhouse or vertical farm, like humans, agribots, animals, and so on and provide a movement pattern of the other object. It is also possible for a LiDAR system to measure the movement and/or location of a plant or product along a moving belt or tray, allowing correct identification of the product.
Furthermore, according to “LiDAR Plant Surveillance”, a method for agricultural management is proposed, which is intended for controlling a controlled agricultural system as described above.
18 th aspect of “LiDAR Plant Surveillance”: More specifically, the method for agricultural management, comprises at least one controlled agricultural system, wherein plants are grown at the growth area, and wherein the plants are captured by a distance measurement performed with the distance measuring device.
19 th aspect of “LiDAR Plant Surveillance”: The method according to the 18 th aspect of “LiDAR Plant Surveillance”, wherein a reference measurement of the growth area ( 203 ) is performed before the plants are grown at the growth area.
20 th aspect of “LiDAR Plant Surveillance”: Computer program product, comprising a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 17 th aspects of “LiDAR Plant Surveillance”, cause the Controlled Agricultural System to execute the Method for Controlling an Agricultural System according to the 18 th or 19 th aspect of “LiDAR Plant Surveillance”.
The growth and health of plants can be monitored according to any of the aspects of the disclosure described above or a combination of various aspects. For example, growth and health of plants may be monitored by combining any or all of the aspects of “Stress Detection”, “Discolored Spots Detection”, “Sensor Retrofit” and “LiDAR Plant Surveillance”. Additionally, potentially critical situations may be detected according to the aspects of “Prophylaxis”. The results of the monitoring, i.e. the probability that something detrimental may have happened to the plants, based on the aforementioned aspects may be further analyzed according to the aspects of “Disease & Pest Control”. Finally, countermeasures may be taken according to the aspects of “Fungi Growth Inhibition”.
Light/Growth Recipes
“Temperature Dependent Illumination”
It is an object to provide an advantageous Agricultural System.
This problem is solved by an Agricultural System comprising at least two light fixtures at different locations and being configured for applying a different illumination with these light fixtures at the different locations based on a temperature value measured. In detail:
1 st aspect of “Temperature dependent illumination”: A Controlled Agricultural System comprising:
at least two light fixtures for providing agricultural lighting, a sensor device for measuring a temperature value, wherein the light fixtures are arranged at different locations in the Agricultural System, and wherein the Agricultural System is configured for applying a different illumination with the light fixtures at the different locations based on a temperature value measured.
›SUMMARY OF THE DISCLOSURE · 36 of 73
The “temperature value” can be the actual temperature, measured for instance in K, ° C. or ° F. The temperature can be measured by any kind of a thermal sensor (Electric, Resistance, Pyrometer, Piezo, etc.). In this respect, the “temperature value” can be any type of output signal of a thermal sensor, which relates to the temperature, for instance an electrical current or voltage. At the “different locations” for instance trays or bowls can be provided, in which the plants are grown. The different locations can in some embodiments/implementations lie on a different height respectively, for instance on different shelfs. In some embodiments/implementations, the different locations are arranged in the same building, particularly preferred in the same room.
Accordingly, the light fixtures and locations can be spaced vertically, for instance in a vertical farm. Vertical farm buildings can have heights of 10, 20, 30 or more meters and contain dozens of shelfs from the ground to the top in which the plants (includes Food Crops, Floriculture, Cannabis ) are growing. Each shelf usually contains its own lighting fixture. Efforts to construct especially designed vertical farms are sometimes summarized under the term Agritecture.
The inventors observed that horticultural light fixtures can produce a certain amount of heat, even in case of LED light sources. The control systems of vertical farms may try to keep a constant (vertical) temperature in the building. However, due to the large number of light fixtures and other electrical equipment producing heat and due to the large dimensions of typical vertical farms, it is unavoidable, that the temperature under the ceiling is higher than on the ground (as warm air is lighter and moves up). Therefore, the temperature conditions in soil and air (and possibly also the water irrigation temperature) is different at different height levels.
Temperature, however, has an influence on the growth of plants. Some plants like petunia or verbena for instance need less time to flowering the higher the temperature is. However, petunia grow faster the higher the temperature is, whereas verbena grow faster the lower the temperature is. Other plants like salvia have a maximum growth rate at about 22° C., whereas they grow slower for higher and lower temperatures.
An approach here is to influence the growth by applying a different illumination depending on the temperature. In particular, the growth at different locations can be synchronized by applying for instance a higher DLI value where the temperature is lower, and vice versa. However, in general, the methodology also allows application of certain lighting conditions at given local temperatures in order to reach other growth targets, like super-fast growth, or super-slow growth for instance (see also “Customer Request”).
2 nd aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to the 1 st aspect of “Temperature dependent illumination”, wherein the illumination applied with the light fixtures at the different locations differs in at least one of a DLI value and a spectral composition.
The “Daily light integral” (DLI) describes the number of photosynthetically active photons (individual particles of light in the 400-700 nm range) that are delivered to a specific area over a 24-hour period.
Further, in terms of the different illumination, different light spectra may be applied at different temperatures. For instance, red light can be of interest at a specific temperature (e. g. 12-19° C.) and blue light at another specific temperature (e. g. 20-25° C.). The red light can affect the activation of phytochrome, the blue light can affect the activation of phototropin and cryptochrome. Additional effects may be generated when applying red or blue light at different humidity levels, e.g. red light irradiation at a cultivation atmosphere humidity level of 40% to 90% and blue light irradiation at a humidity level of 40% to 90%.
Plant growth during various growth cycles can be strongly influenced by the applied light spectra, for example, cucumber and lettuce plants reach greater length and/or mass when illuminated with the inventive horticultural light that includes far red light (700-800 nm).
So, one solution is to adjust the spectral ratios of a horticulture lamp (LED) as a function of ambient temperature. For example, the Far-Red radiation content (better: the Far-Red related Photosynthetically Active Photon Flux Density, PPFD or PFD measured in μmol/(m 2 s), or the Far-Red related Applied Daily Light Integral (DLI) or the Far-Red related Daily Light Applied Spectrum Integral (DLASI), can be properly adjusted, e.g. for every 3° C. temperature increase a reduction of 5-30% compared to the lower temperature level. Of course, as described above, also the DLI values can be additionally adjusted.
3 rd aspect of “Temperature dependent illumination”: A Controlled Agricultural System according to the 1 st or 2 nd aspect of “Temperature dependent illumination”, configured for applying a higher DLI value with the lighting fixture at that location at which the temperature is lower.
4 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to any of the 1 st to 3 rd aspect of “Temperature dependent illumination”, wherein the locations are spaced vertically, namely are arranged on a different height respectively.
5 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to the 4 th aspect of “Temperature dependent illumination”, configured for applying a higher DLI value at that location, which is arranged at a lower height.
Due to the temperature difference in a vertical farm, the growing behavior of plants at higher height levels (especially underneath the ceiling) will differ from the growing behavior on the middle levels or on the ground (at lower temperatures), which will lead to different plant growth morphologies, different harvesting times and possibly also to different plant ingredients (vitamins, THC, enzymes, glucose, etc.) for the same plant. Temperature distribution is of course also influenced by the applied cooling conditions and the day/night illumination cycles (ON/OFF).
›SUMMARY OF THE DISCLOSURE · 37 of 73
A sensor device is provided for measuring the (local) temperature settings, in particular inside a vertical farm building or the like, in order to apply favorable growth influencing conditions (as explained above). Basically, even a single sensor device could be sufficient, for instance an infrared camera allowing a temperature measurement at different locations at the same time. In some embodiments/implementations, a plurality of local sensor devices are provided.
6 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to the 4 th or 5 th aspect of “Temperature dependent illumination”, comprising a plurality of light fixtures on a different height respectively, wherein the Controlled Agricultural System is configured for measuring a temperature value at least at an uppermost and a lowermost location.
Accordingly, all or at least some of the locations can be equipped with a respective sensor device. In particular, the sensor device can be integrated into the lighting fixture. Lighting controllers can be placed locally at the lighting fixture or remotely.
As mentioned, in a vertical farm, a plurality of light fixtures (locations) are provided on a different height respectively, for instance at least 3, 5, 8, 10, 12, 14, 16, 18 or 20 light fixtures (locations). Possible upper limits can for instance be 1.000, 500, 200 or 100 different vertical locations. The vertical locations can be provided on a shelf respectively, each shelf comprising a plurality of horizontal locations on the same height level, equipped with an own lighting fixture respectively.
7 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to the 6 th aspect of “Temperature dependent illumination”, configured for applying, with at least one lighting fixture arranged vertically in between the uppermost and the lowermost location, an illumination based on an interpolation of the temperature values measured at the uppermost and the lowermost location.
It is possible to use a linear (or non-linear) temperature profile by just measuring the temperatures at the bottom and at the top of a building and interpolating in between. Of course, depending on the number of temperature measuring points, any kind of reasonable mathematical interpolation can be used.
Such a desired temperature profile may be dependent on external weather conditions (adjustment time), but this is then already reflected in the actual local temperature measurement. Of course, it is necessary to apply a certain (characteristic) illumination for heat generation, either in a standard setting (DLI, spectrum) or otherwise properly selected. Once measured, such temperature data can be fed into a computer system and proper lighting conditions can be calculated and applied for each plant.
In a basic approach, the temperature profile may only be measured after quite long time intervals like hours, or only once per day.
In a more sophisticated approach, the actual local temperatures (LTik) (I=height index, k=positional index at that height, like position on a shelf) at different elevations (height levels) are regularly measured by various kinds of thermal sensors (Electric Resistance, Pyrometer, Piezo, etc.) and a vertical temperature profile (TPik) can be generated. It is preferred that such temperature sensors are built into the light fixtures.
As mentioned above, measured local data (LTik) can be stored into a Data Bank (DB). Likewise the actually applied lighting conditions (CLik) (either measured or per lighting program/sequence). The measurement of the applied lighting conditions can contain a variety of parameters (DLI, spectral ratios, and so on, as explained above). Measurements can be done e.g. at preselected time intervals (like seconds, minutes, hours), or irregularly. Once measured, such data can be fed into a computer system and proper lighting conditions can be calculated and applied (intermediate approach).
In an even more sophisticated approach, also the actual local plant growth parameters can be measured, like plant height, plant morphology, plant chemistry, plant leaf density index, plant color and other growth and ripening indicative parameters with various measurement techniques (destructive and non-destructive, see for instance “LiDAR for plant measurement” or also “Measuring patterns”). These data will then be stored as well into a data bank (Growth Parameters GPik). The Growth Parameters are compared to target growth values and the proper lighting conditions are chosen to reach the harvesting goal with respect to the actual growth parameters and the actual temperature profile. (high-level approach).
8 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to any of the 4 th to 7 th aspect of “Temperature dependent illumination”, comprising a plurality of light fixtures on a different height respectively, wherein the Controlled Agricultural System is configured for measuring temperature values at all vertical locations to obtain a vertical temperature profile.
9 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to the 8 th aspect of “Temperature dependent illumination”, wherein, on each height respectively, a plurality of light fixtures are provided at different horizontal locations, wherein the Controlled Agricultural System is configured for measuring a temperature value at the horizontal locations respectively to obtain a horizontal temperature profile.
10 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to one of the preceding aspects, wherein at least one of the light fixtures comprises a sensor device for measuring a temperature value at the location of that lighting fixture.
11 th aspect of “Temperature dependent illumination”: The Controlled Agricultural System according to one of the preceding aspects, comprising a computing device, configured to compare the data measured by the sensor device with a reference data set and to apply an illumination based on the result of the comparison.
›SUMMARY OF THE DISCLOSURE · 38 of 73
12 th aspect of “Temperature dependent illumination”: A Method for Controlling an Agricultural System which comprises at least two light fixtures arranged at different locations at which the same plants are grown, the method comprising the steps of
measuring a temperature value at at least one of the locations; applying a different illumination at the different locations based on the temperature value measured.
13 th aspect of “Temperature dependent illumination”: The Method according to the 12 th aspect of “Temperature dependent illumination” for controlling a Controlled Agricultural System according to any of the 1 st to 11 th aspect of “Temperature dependent illumination”.
14 th aspect of “Temperature dependent illumination”: A Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 12 th aspect of “Temperature dependent illumination”, cause the Controlled Agricultural System to execute the Method for Controlling according to the 12 th or 13 th aspect of “Temperature dependent illumination”
15 th aspect of “Temperature dependent illumination”: A Method for Generating a Data Set for a Controlled Agricultural System according to one of the 1 st to 11 th aspect of “Temperature dependent illumination” or for a Method according to the 12 th or 13 th aspect of “Temperature dependent illumination” or for a Computer program product according to the 14 th aspect of “Temperature dependent illumination”, the Method comprising the steps of
growing a plurality of plants and applying a defined temperature and illumination to the plants, wherein, in groups respectively, the temperature and the illumination differs; measuring a growth parameter of the plants respectively.
“Temperature dependent illumination” also relates to a method for generating a data set for controlling an Agricultural System. For generating this data set, a plurality of plants are grown, wherein a defined temperature and illumination is applied. Therein, the temperature and illumination differs in groups. In particular, several different temperatures are defined and several different illumination setups are defined. With each temperature and illumination combination, one or in some embodiments/implementations more plants are investigated by monitoring a growth parameter. In some embodiments/implementations, for generating the data set, conspecific plants are grown and divided into groups with different temperature/illumination.
Such an evaluation can measure and assess for instance the necessary DLI levels (illumination setup) in order to reach the same Time to Flower Rate (growth parameter) at various temperature settings within a given (defined) temperature range, see Table 1 for illustration (for Petunia Coral Pink). Such relationships can be done with all plants and stored into a database. The database then allows producers to adjust the DLI levels (increase, keep, decrease) appropriately in order to synchronize (or at least minimize the time difference) the temperature and DLI-dependent Time to Flower. By the same methodology, however more complicated, also other factors can be taken into account, like Spectral Distribution and its adaptive adjustment, spectral ratios (like UV-B to Far-Red), humidity and others.
16 th aspect of “Temperature dependent illumination”: The Method according to the 15 th aspect of “Temperature dependent illumination”, wherein a correlation function between the temperature and the illumination is obtained from the growth parameters measured.
Apart from the Time to Flower, the “plant growth” measured can for instance also be the plant height, plant morphology, plant chemistry, plant leaf density index, plant color and other growth and ripening indicative parameters with various measurement techniques (destructive and non-destructive). These data will then be stored as well into a data bank (Growth Parameters GP).
Of course, plant growth can depend on many factors that can be evaluated by the method described, like the
i. applied light spectrum, ii. applied Photosynthetically Active radiation (PAR) iii. Photosynthetically Active Photon Flux Density, PPFD or PFD measured in μmol/(m 2 s), iv. applied Daily Light Integral (DLI) or the Daily Light Applied Spectrum Integral (DLASI). v. the change of light spectra, vi. the ratios of spectra e.g. the ratio of blue to Far-Red; or the ratio between UV-A and Far-Red vii. the illumination times with specific light spectra, viii. duration and change between simultaneous or sequential illumination with different spectral distributions, ix. amount and timing of UV-B irradiation, x. day-night-cycles
By the same methodology, however more complicated, also other factors can be considered, like applied temperature periods, i.e. temperature profiles, duration, change and so on. Though complicated, growth influencing relationship can be found. Of course, a variety of mathematical methods and computer simulation including neuronal learning and other artificial intelligence techniques can be used to find proper relations. A skilled person can find out many more of these influencing parameters by proper research.
Of course, it is understood, that the actual local temperatures (LT) are dependent on cooling conditions, air circulation, air humidity, actual light illuminating recipes at each shelf, and so on, generating complex interactive temperature interdependencies with complex feedback loops.
A Data Bank (DB) can for instance hold:
i. Temperature Profiles (LTik, TPik) ii. Lighting conditions CLik iii. Growth Parameters GPik
All these data can be used by a suited computer program (software) to calculate the best Lighting Conditions for the actual local temperature conditions in order to minimize deviation of growth parameters at different local temperatures and/or to influence plant growth otherwise.
The compute unit can also calculate (or extrapolate) time to harvest based on any applied temperature, e.g. a temperature on the ground level of a vertical farm, or on the top level. The compute unit can also communicate this information to third parties: user, provider, etc.
›SUMMARY OF THE DISCLOSURE · 39 of 73
“Adaptive Spectrum”
It is an object of this element of the disclosure to provide an agricultural system or method, which, on the one hand, enables an illumination of the plants with a specific light customized to the respective plant type. On the other hand, it is an object to optimize the energy consumption of the system or facility.
1 st aspect of “Adaptive Spectrum”: A controlled agricultural system, comprising
a growth area for growing plants, a sensor device for a measurement of an ambient spectrum of an ambient light (second light) incident on the growth area, and a light fixture, wherein the agricultural system is configured
to establish a difference spectrum between the ambient spectrum of the ambient light and a target spectrum (third light) on the basis of the measurement of the sensor device, and to trigger the light fixture to emit an additional light (first light) with an additional spectrum,
wherein a superposition (superimposed light) of the first light and the second light is spectrally closer to the target spectrum (third light) than the ambient spectrum.
A respective “spectrum” can for instance cover the entire spectrum or only a spectral range of the respective light. A spectral range can for instance extend over at least 20 nm, 50 nm, or 80 nm (possible upper limits being for instance 1000 nm, 800 nm, 600 nm, 400 nm, or 200 nm). A “spectrum” can be continuous or quasi-continuous, or it can consist of discrete values at discrete wavelengths (e.g. at least one value per nm). For comparing spectra, for instance a radiant flux related value, e.g. the radiant flux itself (in Watt) or the irradiance (W/m 2 ) or radiant intensity (W/sr) or radiance (W/m 2 /sr), plotted over the wavelength (e.g. in nanometer) can be evaluated (plotted in a linear coordinate system). The spectrum resulting from the superposition of the additional and the ambient spectrum, namely the superimposed spectrum, shall be closer to the target spectrum (third light) than the ambient spectrum. In other words, a difference between the target spectrum and the superimposed spectrum shall be smaller than a difference between the target spectrum and the ambient light. Therein, at a respective wavelength, the absolute value (modulus) of the respective difference value is taken.
In some embodiments/implementations, the ambient light is natural light, in particular sunlight. In general, the natural light can be the light available at day or also during the night. In case that sunlight is available, e.g. in terms of daytime and weather, it is incident on the growth area. For this purpose, the growth area of the agricultural system or facility can for instance be a arranged in a glasshouse. However, the sunlight could be also guided to the plants via light tubes or the like.
The sensor device allows for a spectral measurement, namely for measuring a radiant flux related value at different wavelengths. Such a spectral measurement is important, because the growth or thrive of the plants can depend on the flux or intensity in specific spectral ranges, see the “Examples of Light Recipes” below. Measuring for instance only a color of the ambient light would not be sufficient, because different spectral compositions can result in the same color.
2 nd aspect of “Adaptive Spectrum”: The controlled agricultural system of the 1 st aspect of “Adaptive Spectrum”, wherein the superimposed light corresponds to the third light.
As far as possible in terms of technical accuracy, the resulting light (ambient+first light) has the same spectral composition as the target light. In other words, the first spectrum of the first light is basically identical to the difference spectrum.
3 rd aspect of “Adaptive Spectrum”: The controlled agricultural system of the 1 st or 2 nd aspect of “Adaptive Spectrum”, configured for an operation in which the first light has, at least temporarily, a share of at least 10% at the superimposed light.
Further lower limits can for instance be at least 20%, 30%, or 40%. Therein, for instance the irradiance of the first light and the superimposed light are compared. Even though a complete substitution (100%) is possible, preferred upper limits can for instance be 90% or 80% at maximum (at least temporarily, in the supplementation mode). The ambient light (second light) having a certain share at the superimposed light can be advantageous in terms of the energy consumption.
The goal of “Adaptive Spectrum” is to obtain the spectrum of the target light, at least approximately and in some embodiments/implementations to the best possible extent. Only setting the correctly perceived color of the light (given by the color coordinate in a CIE diagram, for example) with the aid of the additional light is insufficient in the agricultural sector; this is because a color can be represented in different ways, i.e., by different spectra (for example, yellow light can be represented by a spectrum of yellow light or by a spectrum containing red and blue components). However, the accurate spectrum is important for the growth of the plants in the agricultural sector.
4 th aspect of “Adaptive Spectrum”: The controlled agricultural system of any of the 1 st to 3 rd aspect of “Adaptive Spectrum”, wherein the light fixture comprises at least two different light sources adapted for emitting light with different spectral properties.
These light sources differ in their spectral properties. Their peak intensities can for instance lie at different wavelengths and/or the spectral distribution can differ (narrowband or broadband). In some embodiments/implementations, the different light sources can be light-emitting diodes, see in detail below.
5 th aspect of “Adaptive Spectrum”: The controlled agricultural system of the 4 th aspect of “Adaptive Spectrum”, the agricultural system being configured for adjusting the intensity of the at least two different light sources individually, namely independently of each other.
Likewise, a very flexible supplementation of the ambient light is possible. In other words, the target spectrum can be reached under various ambient light conditions.
›SUMMARY OF THE DISCLOSURE · 40 of 73
As mentioned, the ambient light can for instance be sunlight. However, it can also be artificial light or a superposition of sunlight an artificial light. Possible fields of application of “Adaptive Spectrum” may for instance be: greenhouses (in particular glasshouses), indoor farming or portable growing units, in which the plants (agricultural plants) are irradiated by a second light which, for example, may be the sunlight and/or artificial illumination (e.g., from adjacent or the surrounding regions, too).
Typically, the second light is not constant. For instance, the sunlight has a certain daily cycle and a yearly cycle, depending on geographic position. Moreover, further influencing variables can influence or change the characteristics of the available sunlight, such as, e.g., the formation of clouds, fine dust, rain, snow, etc. Depending on longitude and latitude, the sunlight has a daily color temperature response. In the morning and in the evening, it has a color temperature of approximately 1800 to 2200 K, it has a color temperature of approximately 5500-6500 K at noon, it has a color temperature of approximately 5500 K at 3.00 pm and it has a color temperature of approximately 4300 K in the evening. The color temperatures lie approximately on or near the Planck curve. The intensity and also the spectrum may change in the case of cloud cover, fog, etc.
The spectral range from 400 to 800 nm is most important for the growth of plants. Said range comprises blue (b) radiation (400-500 nm), green (g) radiation (500-600 nm), red (r) radiation (600-700 nm) and dark red (dr) radiation (700-800 nm). The photon flux (PF) of the photosynthetically active radiation (PAR) emerges from the sum of the individual photon fluxes PFb, PFg, PFr, PFdr. Daylight may have a ratio of PFb:PFg:PFdr=0.27:0.35:0.38.
With the developments of light-emitting diodes (LEDs), radiation sources that emit substantially in monochromatic fashion and radiation sources with a wavelength conversion element (phosphor) have become available. Depending on the embodiment, LED light sources can emit in the ultraviolet, visible or infrared spectrum. The wavelengths of the emission radiation can be accurately set by means of quantum dot LEDs. Organic LEDs (OLEDs), electroluminescence light sources, electrodeless induction lamps and mercury-free dielectric barrier discharge lamps can also be used as a light module. The light sources can have a compact or areal embodiment and can be equipped with primary and secondary optics, such as lenses, light guides, stationary and movable reflectors or radiation-reflective optical devices, holographic elements, partly transparent or completely light-opaque films, heat-reflecting films, luminescent films. Furthermore, use can be made of laser light sources, in particular those that produce white or colored light by means of LARP (laser-activated remote phosphor) technology. Consequently, a multiplicity of light sources are available for illuminating the plants and the entire radiation spectrum (UV, visible, IR) can be covered.
In particular, the agricultural system may comprise a computing device connected to the sensor device. The computing device may be configured to establish the difference spectrum between the spectrum of the ambient light and the target spectrum on the basis of the measurement values of the sensor device. Further, the agricultural system may comprise a control unit, the light fixture being connected to the control unit and the control unit being connected to the computing device. The control unit may be configured to convert the previously established difference spectrum into control signals for the light fixture. Likewise, the light fixture can be triggered to emit the additional light (first light) to supplement the ambient light.
6 th aspect of “Adaptive Spectrum”: The controlled agricultural system of any of the 1 st to 5 th aspect of “Adaptive Spectrum”, configured to restrict an evaluation of the ambient light to wavelengths at which an intensity is designated in the target spectrum.
This can be achieved by a software or a hardware solution. For instance, even the sensor device itself can be configured to restrict the measurement of the ambient spectrum of the ambient light to the different wavelengths.
7 th aspect of “Adaptive Spectrum”: The controlled agricultural system of any of the 1 st to 6 th aspect of “Adaptive Spectrum”, wherein the light fixture comprises LEDs and the agricultural system is configured to restrict an evaluation of the spectrum of the ambient light to intensity maxima of the LEDs of the light fixture.
In some embodiments/implementations, the sensor device is configured to restrict the measurement of the spectrum of the ambient light to these intensity maxima.
It is not the entire spectrum of the available illumination that is measured; instead, the measurement is restricted to the intensity maximums of the LEDs installed in the light fixture. The width of the wavelength range in the measurement may be fixed around the maximum in this case (e.g., +/−25 nm); however, it may also be determined by the curve of the peak, and so the boundaries lie where the intensity has fallen to a certain value ( 1/10 or 1/e) of the maximum.
Now, the actual intensity of the second light is measured in these regions, said intensity is compared to the desired intensity and the intensity of the LEDs can be determined by simply forming the difference.
It is possible to also apply this concept to other reference variables, for example to artificial light sources, the light properties of which change over time and which can be filled accordingly by means of the adaptive additional illumination. Thus, the “ambient light” (second light) can be natural light (direct or indirect sunlight) but also artificial light or a mixture of artificial and natural light.
If the missing parts of the target spectrum (spectrum, light intensity, etc.) are identified in the target area, then it is possible to provide the missing/supplemental parts of the spectrum in a targeted and energy saving manner, said missing/supplemental parts of the spectrum filling the second light spectrally with the desired intensity or further characteristics in order to obtain the target spectrum.
›SUMMARY OF THE DISCLOSURE · 41 of 73
8 th aspect of “Adaptive Spectrum”: The controlled agricultural system as described in any of the preceding aspects of “Adaptive Spectrum”, wherein the sensor device comprises one sensor or a plurality of sensors.
The controlled agricultural system therefore comprises at least one light fixture (agricultural light fixture) with at least one light source and a sensor or an arrangement of sensors (sensor device), by means of which the locally available second light spectrum (in the target area) can be analyzed in respect of composition and intensity, etc. Here, the spectrum means a region from UV to infrared or far infrared, i.e., approximately 100 nm to 100 000 nm (i.e., also including thermal radiation). The spectrum of the available illumination can be analyzed, for example in region increments of 1 nm, of 10 nm or of 50 nm (i.e., it is not the continuous intensity that is recorded; instead, the intensity of the spectrum is digitized in certain ranges).
9 th aspect of “Adaptive Spectrum”: The controlled agricultural system as described in any one of the preceding aspects of “Adaptive Spectrum”, wherein the target spectrum corresponds to a light recipe for irradiating produce, in particular a plant.
Then, the measurement data are compared to the stored reference variables and supplied to a program. The program runs on a computing device, which may be part of the controlled agricultural system or which may else be cloud-based. Moreover, the controlled agricultural system comprises a control unit (light control unit), which actuates the light sources of the at least one light fixture on the basis of the data of the computing device and optionally modifies these appropriately. Here, different light fixtures may also receive different actuation data.
10 th aspect of “Adaptive Spectrum”: The controlled agricultural system as described in any one of the preceding aspects of “Adaptive Spectrum”, comprising an interface for weather forecast data for a predictive adaptation of the additional light to the weather-dependent change in the sunlight (ambient light).
A “prediction” or “predictive adaption” can for instance be based on or implemented by Artificial Intelligence.
11 th aspect of “Adaptive Spectrum”: A method for agriculture, including the following method steps:
measuring the spectrum of an ambient light (second light) incident on a target area, in particular a growth area for growing plants, establishing a difference spectrum between the spectrum of the ambient light and a target spectrum (third light), triggering an emission of an additional light (first light), which has an additional spectrum, wherein a superposition (superimposed light) of the first light and the second light is spectrally closer to the target spectrum (third light) than the ambient spectrum.
For establishing the difference spectrum, the spectrum of the ambient light is compared with the target spectrum (spectrum of the third light). The first light emitted then has, at least approximately, the spectral composition of the difference spectrum to fill this gap. In particular, this can be achieved by way of a suitable actuation of a light fixture. Then, the growth area (target area) is irradiated with the produced additional light, in addition to the ambient light.
The spectrum of the second light (ambient light) is compared to the spectrum of the target light that should be used to illuminate the plants. Ideally, the spectrum is available using the same type of description as the measured spectrum, in this example as intensities in a wavelength range (if the spectrum is available as a continuous spectrum, the corresponding value can easily be calculated by way of the area of the intensity present in this wavelength range). Thus, the differences in the intensity can be determined for the individual ranges (e.g., using the method of least squares) and the control unit can actuate the light fixture accordingly so that the plants are irradiated by the required intensity in the determined wavelength ranges. Thus, the light fixture provides an additional light (=first light), which complements the second light (the already available ambient light) to form the target light. Moreover, provision can be made for the additional light to be adapted to the spectral changes of the ambient light (e.g., path of the sun, seasons, etc.) and/or of the predeterminable target light.
Apart from the spectral properties, also other light parameters can be measured, for instance the polarization and/or irradiation angle.
12 th aspect of “Adaptive Spectrum”: The method as described in the 11 th aspect of “Adaptive Spectrum”, including the additional method step of:
measuring the spectrum of the additional light, comparing the spectrum of the additional light to the established difference spectrum, adapting the spectrum of the additional light if the deviation between the measured spectrum of the additional light and the difference spectrum exceeds a tolerance range.
The spectrum of the second light can be measured with spatial resolution over the irradiation surface and the respective differences to the respective local target light can be calculated, for example using the method of least squares. Local differences can likewise be averaged in order to establish an overall difference for the entire illuminated region and in order thus to set the first light accordingly. In addition to local averaging, provision can also be made for an averaging of the individual differences and of the overall difference over time.
The sensor or sensors can also measure the light of the light fixtures. To this end, the light fixture radiation can be briefly modulated, for example, and so a measuring device can distinguish the artificial light from the natural light. This can ensure that the light output by the light fixture corresponds to the desired difference between the second light and the target light. If this is not the case, there is a corresponding correction (i.e., the intensity of the corresponding LED of the light fixture is adapted).
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13 th aspect of “Adaptive Spectrum”: The method as described in the 7 th aspect of “Adaptive Spectrum”, wherein the additional light is modulated during the measurement of the spectra for the purposes of distinguishing it from the ambient light.
The measurement of the spectrum of the second light and thesssss calculation of the additional light can be implemented after certain time intervals, for example every second, every minute, etc. The time interval can be designed differently depending on, e.g., the color temperature or other influencing variables (light intensity, polarization, weather).
The spectrum of the additional light (first light) can be adapted as soon as the spectrum of the target light and the spectrum of the second light differ or the measured spectrum of the additional light and the difference spectrum differ, or else only once the difference exceeds a tolerance range.
In a further configuration, it is possible to take account of not only the current spectrum of the second light (i.e., the ambient light) but also a prediction in the light change when creating the first light (i.e., the additional light/light fixture light). For the good growth of the plant, also receiving the necessary daily light integral (DLI) in addition to the correct spectrum over the day is important. To this end, the controlled agricultural system can obtain information about a weather forecast (data provided by a weather station), and so the further change in the second light can be predicted (i.e., the system has an interface to a weather forecast provider). For example, should the forecast suggest that it will be cloudy during the day, irradiation of the plants can already be started at an earlier time, for example already at 4 o'clock with primarily red light.
“Flexible Growth”
In automated plant production (e.g. in a greenhouse or in a vertical farm), one or more control units can regulate or control the plant production, for example the production process (planting, fertilizing, watering, illuminating, quality monitoring, etc.).
Further examples of processes that can be controlled by control units are the ordering process for precursor materials (seeds, fertilizer, etc.), the supply-demand requirements (customer wishes, customer orders, delivery dates and on-time delivery, cancellations, complaints), and taking account of economical and ecological points of views (e.g. energy consumption, goods storage and delivery). Respective control units may also be combined in a superordinate control unit, which then consists of a plurality of such sub-system units, such as, e.g., an interface to the customers (order and delivery platform, complaints, cancellations), an interface to the energy producers (cost control, energy availability), an interface to the actuation unit for the light fixtures or the applied light programs (growth-dependent illumination recipes), an interface to the precursor material suppliers, an interface to the transport and storage logistic companies, an interface to a data acquisition and evaluation unit (computing center, software), and more.
The growth behavior of the products, the yield (mass, number) and for example a target time, e.g. the harvest or delivery time can be predicted. Such a prediction can be possible based on growth recipes defining growth parameters, as for instance the growth cycle as a fixed parameter.
However, as discussed in “Flexible Growth”, it could be interesting to adapt the target time, e.g. harvesting time, in line with external requirements arising for instance in the supply chain. It can be an interesting approach to consider for example the workload in downstream facilities (food producers) but also in upstream facilities (precursor materials).
1 st aspect of “Flexible Growth”: A Method for operating a controlled agricultural system, wherein
plants are grown, a growth recipe is applied to the plants, wherein the growth recipe delivers a growth cycle, namely a target time for the growth of the plants, and wherein further the growth recipe is amended prior to reaching the target time; wherein, due to the amendment of the growth recipe, i) the growth cycle is shortened or extended, and ii) a quality value of the plants is altered, and/or iii) a production value of the agricultural system is altered.
In a sense, the measures or results of the items i) to iii) are conflicting targets. For instance, assuming that iii) remains unchanged, an improvement of item i), namely a shortening of the growth cycle, will result in a deterioration of a quality value, for instance in terms of the plant's color or morphology. The approach of “Flexible Growth” is to consider or take into account these interdependencies of the different measures and to amend the recipe, e.g. depending on external requirements. Such requirements can for instance be the workload in a subsequent facility processing the crop or the crop quality required currently in such a facility (which can vary and depend e.g. from the crop quality of other farms).
2 nd aspect of “Flexible Growth”: The Method of the 1 st aspect of “Flexible Growth”, wherein a quality value of the plants is altered, namely a vitamin content, a color parameter, or a morphology parameter.
For instance, the vitamin content can be increased to compensate a poor crop quality of another farm. On the other hand, a reduced vitamin content could be found to be acceptable in case that the growth cycle shall be shortened, e.g. to optimize the workload in the supply chain. In general, shifting the target time, in particular the harvest time, can for instance help avoiding overcapacities and undercapacities in the supply chain. A product (fruits, vegetables, cut flowers, medical plants) may be required earlier, or else later. Although, alternatively, a delay could be offset by storage, a disadvantage arising in the process could be that contents are degraded, i.e. the quality suffers.
3 rd aspect of “Flexible Growth”: The Method of the 1 st or 2 nd aspect of “Flexible Growth”, wherein a production value of the agricultural system is altered, namely an energy consumption of the agricultural system.
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4 th aspect of “Flexible Growth”: The Method of the 3 rd aspect of “Flexible Growth”, wherein the growth cycle is shortened and a production value of the agricultural system is impaired.
5 th aspect of “Flexible Growth”: The Method of any of the preceding aspects of “Flexible Growth”, wherein the growth cycle is shortened and a quality value of the plants is impaired.
Impairing a color parameter can for instance mean that a leaf or fruit color pales, for example from green or red to a pale color tone. Impairing the vitamin content means that less vitamins are contained in the plants, and impairing a morphology parameter can for instance mean that the stem diameter is reduced or the branching is negatively affected.
6 th aspect of “Flexible Growth”: The Method of any of the 1 st to 3 rd aspect of “Flexible Growth”, wherein the growth cycle is extended.
Usually, keeping the growth cycle as short as possible is a superordinate target in agriculture. In this case, it is intentionally extended, for example to avoid overcapacities and undercapacities in the supply chain, see above.
7 th aspect of “Flexible Growth”: A controlled agricultural system for making plant growth flexible, comprising
an acquisition unit for acquiring the change of the delivery date for a product of a plant, actuators configured to act on the plant growth, a control unit connected to the actuators and configured to identify the plants affected by the change in delivery date, a computing device connected to the acquisition unit and the control unit and configured to establish modified control parameters for the actuators on the basis of the determined current growth status in such a way that the desired state (degree of maturity) of the product is obtained at the time of the amended delivery date.
8 th aspect of “Flexible Growth”: The controlled agricultural system of the 7 th aspect of “Measuring Patterns”, the computing device being configured for executing a method according to any of the 1 st to 6 th aspect of “Flexible Growth”.
The embodiment facilitates monitoring and control of the growth of the plants. To this end, the controlled agricultural system comprises a control unit, which monitors and controls the growth of the plants. As a result, it becomes easier to flexibly react to changes in customer queries and to adapt the harvest time or delivery date. A digital supply chain (software platform) can be filled depending on the customer queries and dates, and plants are planted so that they are mature in timely fashion. Here, the supply-demand interface can serve as a marketplace, in which supply and demand are matched to one another and the market prices are established. The platform closes contracts and ensures transparency along the supply chain.
The change in target time can be triggered by an amended customer query. Depending on the notice for the change in delivery date, it is possible to delay or accelerate germination, growth or maturing of the product. This is implemented by way of suitable changes of, for example, parameters such as light spectra, light intensity, CO 2 content, water/nutrient supply or temperature (air, water, ground, plant root, plant blossom, plant leaves, etc.) by way of suitable actuators (such as light fixtures, watering facilities, heaters, cooling devices, fertilizer applicants). In the case of a change in the customer-related delivery date, the plants affected thereby are identified by the control unit. To this end, whole growing units (in the case of a large order, for example) can be provided with an ID, for example a QR code, but also the smallest individual sale units, such as plant pots, planting bowls, etc.
9 th aspect of “Flexible Growth”: The controlled agricultural system of the 7 th or 8 th aspect of “Flexible Growth”, comprising
sensors connected to the control unit and configured to determine the growth phase of the plants.
Moreover, the growth phase of these customer-related plants or the amount of, e.g., light and/or temperature that they have already taken up, for example also temperature without light, i.e., in darkness, are determined. The individual values, the number of individual values or else the sum of individual values (time integral, power integral) are acquired in the process. Here, the acquired information items can be very multilayered since growth-related parameters are a function of a plurality of influencing factors, such as for example: applied light spectrum, applied photosynthetically active radiation (PAR), applied photosynthetically active photon flux density (PPFD or PFD, measured in μmol/(m 2 s)), applied daily light integral (DLI) or daily light applied spectrum integral (DLASI), or the ratios of the spectral intensities of blue to dark red, or of UV-A to dark red, the number and duration of the changes between two different illumination states, the radiation dose of UV-A and UV-B radiation, and many more.
These information items can be kept in a growth log for each growing unit. In order to determine the current growth phase, provision may also be made of optical sensors, for example cameras, or else other sensors such as chemical sensors, spectrally sensitive sensors or thermal sensors. Here, the phrase growth phase comprises all stages of the plant growth, including the maturing of possible fruits (e.g., fruit, vegetable, fungi, plants, etc.) of the plant.
Moreover, the amounts still required by the plants or grown products, for example in respect of the irradiation (spectral photon fluxes) and/or temperature and dark times (see above in respect of further influencing factors), until they have reached the state provided for delivery (e.g., customer-specified degree of maturity) are determined.
10 th aspect of “Flexible Growth”: The controlled agricultural system of any of the 7 th to 9 th aspect of “Flexible Growth”, wherein the computing device is connected to a database which, for a respective plant, stores what change of a control parameter can bring about a certain delay or acceleration or standstill of the growth.
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The running control program is interrupted and replaced by a delay or acceleration program, or holding program, which use parameters (spectrum, temperature, CO 2 and more) that have been modified on the basis of the values established above in order to correspondingly delay or hold the growth of the plants (later delivery date) or accelerate this (earlier delivery date). Here, the computing device of the controlled agricultural system in some embodiments/implementations accesses a database that has available appropriate plant-specific information items (e.g., a change in the parameter x leads to delay of the growth by y hours). From these information items, the computing device calculates a suitable modification of the parameters in order to produce the desired acceleration or delay, or the desired holding state, of the plant growth. In this calculation, it is possible to take account of which plant parameters (color, size, content, etc.) were particularly important to the customer such that the newly calculated parameters do not change these plant parameters where possible (keeping customer-critical plant parameters).
Acceleration programs can be accompanied by a higher light dose (e.g., a higher DLI, see above) and/or a higher proportion of red and dark-red radiation. Acceleration programs may also use other dark periods, e.g., shorter dark periods, and also set or change brief irradiation during dark periods. Acceleration programs can increase the nutrient supply and the fertilizer supply, and also appropriately adapt watering, ventilation, room temperature, etc.
Delay programs can be accompanied by a lower light dose (e.g., a lower DLI, see above) and/or a lower proportion of red and dark-red radiation. Delay programs may also use other dark periods, e.g. longer dark periods, and also prompt or modify the brief irradiation during dark periods. Delay programs may reduce the nutrient supply and the fertilizer supply, and also appropriately adapt watering, ventilation, room temperature, etc.
Holding (standstill) programs modify the parameters in such a way that the current state of the plants is largely maintained.
Depending on the shift in date, a calculation is carried out as to how long the modified control program should be used until the standard control program can be used again. Optionally, the modified control program is also used until harvest.
11 th aspect of “Flexible Growth”: A method for agriculture, comprising:
a controlled agricultural system as described in any one of the preceding aspects and the following method steps: acquiring the change in the delivery date for a product of a plant with the aid of the acquisition unit, identifying the affected plants with the aid of the control unit, and determining the current growth status of the affected plants with the aid of the sensors or by way of the growth log, calculating the modified control parameters by the computing device on the basis of the determined current growth status and the state of the product to be obtained at the time of the modified delivery date, actuating the actuators with the modified control parameters by the control unit (acceleration or holding or delay program).
12 th aspect of “Flexible Growth”: The method for agriculture as described in the 11 th aspect of “Flexible Growth”, wherein
the modified control parameters are calculated in such a way that they delay or accelerate the germination, the growth or the maturing of the affected plants or of the product (fruit) of the plants.
The market prices (supply-demand) can be noted at regular intervals and the control program may be updated accordingly under certain circumstances. Conceivable scenarios include:
If an order is canceled and another customer whose order data can be met with a modified growth program (control program) is found, the modified growth program (control program) is applied. If another customer is found and there still is sufficient time for a new seed in respect of the modified customer order, there is no delay, but the new customer is served. In particular, this may be the case if the new customer does not require mature plants at all but only cuttings. Then, a new production is carried out for the modified customer order. If need be, the first production can be accelerated for the other customer and the original customer can be served with a likewise accelerated, subsequent production.
13 th aspect of “Flexible Growth”: The method for agriculture as described in the 11 th or 12 th aspect of “Flexible Growth”, including the additional method steps of:
observing the market conditions, adapting the delivery date to the current market conditions.
14 th aspect of “Flexible Growth”: A method for agriculture if the original purchase date for a product is delayed by the customer, including the following method step:
calculating whether a slowdown of the production or storage of the finished products would be more cost-effective.
It is also possible to calculate whether a delay of the production or storage would be more cost-effective. Possibly, the production is then carried out as planned and stored since a delay additionally occupies the production area (opportunity costs).
It is also possible to calculate whether a production can be influenced in corresponding fashion at another automated plant production and can be assigned to the customer order.
“Plant Movement”
1 st aspect of “Plant Movement”: An Agricultural Light Fixture, particularly for use in a Controlled Agricultural, comprising:
multiple light modules, each light module comprises at least one light source and at least one driver connected to the at least one light source; wherein the light modules are controllable individually or in groups.
Plants need nutrients and light to grow. However, to grow strong, they also need to move to strengthen their stems or shoots, in particular the stem fibers. One possibility to induce a movement is to create a certain airflow or wind gusts in a greenhouse or a vertical farm, which simulates the airflow that plants would experience in an open field.
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Phototropism is the influence of light on the growth of plants. It can be positive, like for sprouts, or negative, like for roots, i.e. the plants (stem, leafs, blossom) can move and/or bend towards the light or away from the light respectively. Plant growth, growth direction and morphology can also be influenced by irradiation the plant with polarized light.
It is not only that the light fixture or fixtures can illuminate the plants alternatively from opposite directions or be moved linearly across a plant growth area, but that also the intensity and/or of the illumination spectrum can be changed, in particular both together. This can be done with the whole lighting fixture arrangement or also a single light fixture, in order to maximize a phototropic effect in combination with or as a function of plant growth, plant morphology and plant ripeness.
2 nd aspect of “Plant Movement”: The Agricultural Light Fixture according to the 1 st aspect of “Plant Movement”, wherein at least one light module is configured to be able to emit light with various intensities and/or spectra.
The maximum intensity values at both sides of the agricultural light fixture or a fixture arrangement can be adjusted to the needs of the plants; the intensity values do not need to be equal at both sides but can vary over time
Furthermore, the agricultural light fixture may be configured to have two different intensities: One maximum intensity and one “standard” intensity (which is lower than the maximum intensity). The agricultural light fixture may as well be configured that its intensities can change gradually between a maximum and a minimum value. The difference between maximum and minimum needs to be sufficient to activate the phototropism of the plants. Furthermore, the values for maximum and minimum intensity and their respective durations may be adapted to the required DLI (day light integral) for each plant.
Furthermore, the agricultural light fixture may comprise multiple areal sections that are configured to emit light with different intensities and/or spectra. There could be a left section of the light fixture with a first lighting setting, for example to irradiate plants in the morning cycle with light having a reddish color temperature at about 4000 to 2000 K, a middle section that emits light with a midday daylight having a color temperature of 5000 to 10000 K, and a right section that emits light with a color temperature of about 4000 to 2000 K (sunset condition), depending on the geolocation.
Furthermore, the left and right sections of the agricultural light fixture may be configured to be able to incline or adaptively incline in order to emit light to the plants at a certain (varying) irradiation angle thus mimicking the position of the natural sunlight (circadian condition). Of course, similar cycles may be applied during the night, mimicking moon and starlight.
Furthermore, the agricultural light fixture may be configured to enable changing the form or inclination of the light fixture or of moveable parts of the light fixture in order to change the incoming beam inclination angles and/or distance to the plant within a given lighting period.
3 rd aspect of “Plant Movement”: The Agricultural Light Fixture according to the 1 st or 2 nd aspect of “Plant Movement”, wherein at least one light module comprises an LED or LED-module.
In a preferred embodiment, the agricultural light fixture comprises LEDs or groups of LEDs, which can be controlled independently in order to enable the local intensity change over time. If the agricultural light fixture is configured such that single LEDs can be controlled, a gradual change of intensity is possible, if only groups of LEDs can be controlled, only a stepwise (specific lighting emitting areas) change of the intensity is possible. The groups of LEDs may be LED modules arranged in the agricultural light fixture. It is also possible to use several agricultural light fixture near each other (arrangement of agricultural light fixture) to realize this local intensity change over time.
4 th aspect of “Plant Movement”: A Controlled Agricultural System, comprising
at least one agricultural light fixture according to one or more of the preceding aspects, wherein the Controlled Agricultural System is configured for controlling the light modules individually or in groups.
5 th aspect of “Plant Movement”: The Controlled Agricultural System ( 200 ) according to the 4 th aspect of “Plant Movement”, wherein controlling the light modules ( 110 ) comprises controlling the intensities and/or the spectrum of the light emitted by respective light modules ( 110 ).
6 th aspect of “Plant Movement”: The Controlled Agricultural System according to the 4 th aspect of “Plant Movement”, wherein the controlling of the light modules is coordinated such that the at least one agricultural light fixture is able to emit light with an intensity distribution comprising a maximum light intensity.
Therein, the intensity in distributed locally across the light fixture(s), giving a spatial intensity distribution. To induce a (bending) movement of plants using light, the intensity and/or the spectrum of the illumination is changed locally, i.e. across a part of an illuminated cultivated area (target area), over time, thus irradiating a plant from different, in some embodiments/implementations opposite, directions and/or illumination angles.
7 th aspect of “Plant Movement”: The Controlled Agricultural System according to any of the 4 th to 6 th aspect of “Plant Movement”, wherein the controlling of the light modules is further coordinated such that the at least one agricultural light fixture is able to move the maximum light intensity with respect to the light emitting surface of the agricultural light fixture.
As an example: Luminaires used in indoor farms usually have an elongated rectangular form, with one side being longer than the other side. In an exemplary embodiment of an agricultural light fixture or an arrangement of agricultural light fixtures according to “Plant Movement”, the intensity of the light on the right side may be stronger than on the left side (for instance) at the beginning of the daily illumination period. Then the maximum of the intensity moves towards the left side during the day so that the intensity is stronger at the left side than on the right side at the end of the daily illumination period. Of course, any other rhythm can be chosen, i.e. once per hour, every 6 hours, every 10 hours, every 14 hours. In some embodiments/implementations, the rhythm is an integer factor of the daily illumination period. Alternatively, the agricultural light fixture may be configured that the maximum intensity moves from right to left and back from left to right during one period (although the light patterns can be different).
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8 th aspect of “Plant Movement”: The Controlled Agricultural System according to any one of the 4 th to 7 th aspect of “Plant Movement”, wherein the controlling of the light modules is further coordinated such that the at least one agricultural light fixture is able to move the maximum light intensity from one light module (M 3 ) to another light module (M 4 ).
9 th aspect of “Plant Movement”: The Controlled Agricultural System according to any one of the 4 th to 8 th aspect of “Plant Movement”, further comprising a control unit configured for controlling the light modules of the at least one agricultural light fixture.
In general, the controlled agricultural system may also comprise light guides and/or light reflecting plates, which may be activated or deactivated at certain times and moved in certain positions (height, inclination) with respect to the plant canopy and to provide plant central and/or side illumination (including root lighting). This way, light can be directed to irradiate the plants from different sides or angles and therefore contributes to the described inventive aspect. Activation means to allow light to pass into or onto these guides/plates and/or to activate special light sources that illuminate these light guiding elements.
Furthermore, the agricultural light fixture may be configured to enable changing the spectral composition of light, particularly as a function of the moving location of the maximum value of the light intensity with respect to the light emitting surface. The spectrum may be changed as a function of the intensity or the intensity can be changed as a function of the spectrum during a period. It is also possible that different relation of spectrum and intensity are applied in different periods, e.g. if a period has a length of 4 hours and the daily illumination is 12 hours, then each of the 3 periods could have a different relation of spectrum and intensity.
In a further refinement of “Plant Movement”, that comprises a changing spectral composition of light, a cycle that resembles the circadian cycle for sun light and/or a cycle for moon light is applied to the movement of the maximum value of the light intensity.
Furthermore, the light sources that are used for a time-specific maximum light intensity may be operated (at least for certain time intervals) in a pulse mode fashion. The cycles may be determined by the geolocation.
Furthermore, the intensity change of the LEDs or LED modules arranged in the agricultural light fixture may be non-periodic or stochastic.
10 th aspect of “Plant Movement”: The Controlled Agricultural System according to the 9 th aspect of “Plant Movement”, further comprising
a computing device, coupled to the control unit, data storage device, coupled to the computing device, for storing the controlling schemes for the light modules, wherein the computing device is configured to control the light modules of the at least one agricultural light fixture via the control unit, based on the data of the controlling schemes stored in the data storage device.
The computing unit may also be configured to take into consideration the applied light or growth recipes.
Another approach would be to rotate the plants and keep the luminaire static. Rotating could mean to move the plants around the vertically arranged luminaire (e.g. on a circle with the circumferentially illuminating luminaire at its center) or the plants could turn around a central axis thus exposing all sides to the luminaire in a given timeframe. Alternatively, the luminaire may be horizontally arranged and the plants may rotate such that alternately the upper side and the lower side of the plants are illuminated.
11 th aspect of “Plant Movement”: A method for agricultural management, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, e.g. a plant growing facility, comprising the steps of:
Providing multiple light modules, which can be controlled individually or in groups, Arranging the multiple light modules above the plants arranged in a target area and illuminating the target area, Controlling the light modules to emit light on the target area having an light intensity distribution that comprises a maximum light intensity, Moving the maximum light intensity within the target area.
12 th aspect of “Plant Movement”: The method for agricultural management according to the 11 th aspect of “Plant Movement”, whereby the multiple light modules are arranged in a row and are controlled such that the maximum light intensity moves from one light module in the row to another light module in the row.
13 th aspect of “Plant Movement”: The method for agricultural management according to the 11 th or 12 th aspect of “Plant Movement”, whereby the maximum light intensity of the light intensity distribution is implemented by controlling at least one light module or at most a subset of the multiple light modules of the light fixture such that its light intensity is higher than the light intensity of at least one other light module illuminating the target area.
14 th aspect of “Plant Movement”: The method for agricultural management according to any one of the 11 th to 13 th aspect of “Plant Movement”, for controlling a Controlled Agricultural System according to any one of the 4 th to 10 th aspect of “Plant Movement”.
15 th aspect of “Plant Movement”: A method for agricultural management, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, e.g. a plant growing facility, comprising the step of:
Moving the plants with respect to a horticulture light fixture such that all circumferential sides of the respective plant is illuminated by the horticulture light fixture during a specified timeframe (cycle time).
16 th aspect of “Plant Movement”: The method for agricultural management according to the 15 th aspect of “Plant Movement”, further comprising the step of rotating the plants around a central axis.
17 th aspect of “Plant Movement”: A computer program product, comprising:
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a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 4 th to 10 th aspect of “Plant Movement”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 11 th to 13 th aspect of “Plant Movement”.
“Spectrum Calculation”
A light recipe can define the photon fluxes in all defined spectral ranges of a light source arrangement of a light fixture ((agricultural) light fixture) at a given time. It can contain a temporal sequence of photon fluxes in all defined spectral ranges, a sequence of ON or OFF illumination states and a program for the dynamic creation of light recipes. Furthermore, a light recipe can set modes of operation of an illumination device, for example constant power operation, pulsed operation, DC operation or AC operation. Furthermore, a light recipe can be generated from a calculation method with the aid of artificial intelligence (AI), for example by virtue of a plant-related assessment scheme of operation and sensor data being created and a light recipe then being generated therefrom and being applied to the illumination devices. Furthermore, a light recipe can not only set the spectral intensities of the light module but can also define the emission characteristics (e.g., beam width, emission angle, polarization) in cooperation with optical elements (e.g., lenses, mirrors, polarizers). Light recipes can also be created in customer-specific fashion. Thus, the light recipes define the optimal spectrum or a (non-ideal) spectrum that approximates an optimal spectrum for an envisaged application. This spectrum can be present as a continuous intensity distribution over the wavelength (or wavenumber), or else as a discrete intensity distribution over certain spectral ranges, wherein the spectrum or spectrums is/are able to be set in a variable, i.e., changeable, manner. Light recipes can also be created under inclusion of local light conditions, for example in the case of a greenhouse illumination (greenhouse lighting).
By way of example, the intensity in the blue range from 400-450 nm should have a certain value, a further value in the range from 450-500 nm and a third value in the range from 600 to 720 nm. A value can have a respective overall radiant flux or a respective PPF (photosynthetic photon flux, i.e., photon flux in the photosynthetically active region (PAR)) value or a respective PPFD (photosynthetically active photon flux density (μmol/(m 2 s))) value.
Additionally, the photon flux ratio of spectral range 1 (e.g., blue) to spectral range 2 (e.g., red) and to further spectral ranges can be defined by a light recipe (constant in time or changeable). Naturally, this also applies to any other formation of ratios of spectral ranges (UV, VIS, IR, dark red).
Now, a light recipe can be created for a defined selection (number, arrangement) of light sources. It then controls the activation and deactivation of the light sources.
Now, plant illumination devices can have a different number and arrangement of light sources. Then, there is the need to convert a light recipe, or adapt it to the best possible extent, for other plant illumination devices (light fixtures) with a different number and arrangement of light sources.
The illumination used to illuminate the plants in some embodiments/implementations has LEDs. Here, use can be made of LEDs with different colors, and also in the UV and infrared. The LEDs can be directly emitting or phosphor converted (phosphor converted LEDs: pc-LEDs). Directly emitting LEDs have narrowband spectra with discrete maxima, in which their light intensity is highest. Phosphor converted LEDs have broader spectral ranges with an intensity maximum. The width of a maximum can be defined by way of the FWHM (full width at half maximum) or else by way of the reduction of the intensity at the maximum to (1/e) 2 . Then, the maximum can be known or determinable as a single value, for example 525 nm.
Consequently, both the spectrum and the spectral ranges in which the spectral maxima lie, and also the maximum values themselves, are known for each LED type. The overall spectrum of the light fixture emerges from the superposition of the spectra of the individual LEDs. A superposition of the spectra can be implemented both in real space and in angle space.
Consequently, the corresponding data are also known for a plant illumination device, and also (where necessary) the data of the geometric arrangement of the light sources and the light fixtures.
1 st aspect of “Spectrum Calculation”: A controlled agricultural system facilitating the use of a light recipe with different light fixtures, comprising
a light fixture with a plurality of light sources, an acquisition unit for capturing parameters of the light fixture and of a light recipe, a computing device connected to the acquisition unit, a control unit connected to the computing device and the light fixture, said control unit configured to convert the data of the computing unit into control signals for the light sources of the light fixture such that the light fixture produces radiation, wherein the computing device is configured to select the suitable light sources from the light sources present in the light fixture and calculate the actuation thereof on the basis of the parameters of the light fixture in such a way that the radiation of the actuated light fixture at least approximates the light recipe.
An object here is to allow a light recipe to be used or adapted in a controlled agricultural system in the case of light fixtures (agricultural light fixtures) of different design. Thus, inter alia, a solution is proposed of how a light recipe can be used, for example, both in the case of a light fixture which only has three different LED colors (e.g., blue, red, dark red) and in the case of a light fixture that has seven different LED colors (e.g., dark blue, light blue, yellow, orange, red, dark red, green). However, the approach is also applicable to nonvisible spectral ranges, such as ultraviolet and infrared, to be precise in combination with visible colors and independently.
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2 nd aspect of “Spectrum Calculation”: The controlled agricultural system as described in the 1 st aspect of “Spectrum Calculation”, comprising two or more light fixtures,
wherein the light sources in the at least two light fixtures differ in one or more of the following criteria: number, maximum intensity, wavelength at the maximum of the emission radiation, spectral width of the emission radiation, spatial distribution of the radiation, angle distribution of the radiation, type of light source.
Thus, the light recipe may be available for a light fixture with a certain combination of LEDs and it should now be used for a light fixture containing the same type of (structurally equivalent) LEDs, albeit in a greater respective number. Thus, for example, a light recipe is designed for maximum emissions of 3 blue and 4 red LEDs of a first light fixture and it should be used in a second light fixture with 4 blue and 5 red LEDs which are structurally equivalent in each case (excess number of in each case structurally identical light sources), then
only 3 of the 4 blue LEDs and only 4 of the 5 red LEDs of the second light fixture can be used when applying a respective maximum power or the light power of the 4 blue LEDs of the second light fixture is reduced overall by a factor of ¾ (i.e., by 25%), wherein the individual LEDs of the 4 blue LEDs may be actuated differently and the reduction factor of ¾ must only arise in the sum; and the 5 red LEDs must be impinged by the overall factor of ⅘ (i.e., a reduction by 20%). Thus, the light power is reduced by the ratio of the original number of LEDs and to the new number of LEDs. A change in the light power, suitable to this end, by way of the current (increase, decrease) or a modulation of the operational data is known.
If a fewer number of light sources (e.g., LEDs) of the same design in each case are present in the second light fixture, the fewer number must have a stronger electrical impingement by a factor; i.e., in the case of X blue LEDs of the first arrangement and Y (less than X) blue LEDs of the second arrangement, the Y blue LEDs must be impinged more strongly by a factor of X/Y. A change in the light power, suitable to this end, by way of the current (increase, decrease) or a modulation of the operational data is known.
Should a higher impingement prove impossible (operational safety, service life of the LEDs), then, optionally, the light recipe may be modified and/or the associated irradiation may be applied for longer. An analogous statement also applies in the first case, if a reduction in the operational values is not possible (then, where applicable, the light recipe would have to be applied for a shorter time (provided this is beneficial to the product)).
Naturally, this method also applies to other configurations of structurally equivalent LEDs.
3 rd aspect of “Spectrum Calculation”: The controlled agricultural system as described in the 2 nd aspect of “Spectrum Calculation”,
wherein the computer device is configured to respectively calculate a selection of the light sources for the light fixtures with various light sources and the actuation thereof in such a way that the radiation of the various light fixtures at least approximates the light recipe.
An approximation method is used should a situation arise in which the second light fixture does not comprise structurally equivalent light sources, e.g., LEDs, i.e., in which said second light fixture cannot exactly reproduce the predetermined light spectrum. To this end, the light sources used in the respective light fixture, the number of said light sources, operational data, spectral data and maximum values being known to a control unit of the light fixture, are transmitted to a computing device (software program), which then is able to simulate a variation space of all (or most) possible spectral combinations (simulation points). These simulation points are then compared to the target spectrum or target data of the light recipe, for example using the method of the least squares between calculated simulation points and target data, or of the smallest distance from the overall CIE value of the target light recipe, or of the spectral-range-specific photon fluxes. Then, the configuration (operation of those light sources of the second light fixture) which is closest to the target spectrum or the target data is selected. This setting can be adapted during the scope of the irradiation duration to the requirements of the products (growth, morphology, maturing).
These methods described in 1. to 3. can be applied both to light recipes that are not changeable in time and to light recipes that are changeable in time. Furthermore, the methods described in 1. to 3. can also be used for different types of light sources, for example the combination of organic LEDs (OLEDs) with inorganic LEDs, or with inclusion of LARP (laser-activated remote phosphor) light sources, and with inclusion of conventional light sources such as discharge and incandescent lamps.
Furthermore, it is possible to prescribe limits for the allowed deviations in the respective spectral ranges. This is due to the fact that some ranges of the spectrum (e.g., in the blue and in the red and also in the green when producing plant-based content) are particularly critical for the quality of a plant, for example when forming enzymes, vitamins, etc. Here, for example, even a small deviation of the light power can lead to relatively large changes (morphology, nutritional value) in the plant.
Consequently, a method is provided, by means of which a light recipe, which has been defined for a light fixture, can be transferred to a second light fixture of a different design. To this end, the respective light fixture parameters (number and type of the light sources, possibly also the arrangement thereof and the type and arrangement of optical elements) are made available to a control unit (light control unit) or a computing device of the light fixtures or of the controlled agricultural system. Here, the computing device may also be referred to as a “transformation unit”, since it transforms a light recipe into another light recipe that is as equivalent as possible, i.e., it makes a light recipe applicable to a second light fixture of a different design. To this end, the method according to this element of the disclosure includes a transformation prescription, which, based on the light fixture parameters, undertakes the transformation of a light recipe for a first light fixture to a light recipe for a second light fixture that differs from the first light fixture. A transformation matrix can be stored and distributed in a data network. Here, a first light fixture and a second light fixture can be spatially separated, for example at different locations in irradiation devices in plant breeding and/or growing facilities.
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In a further configuration, this method renders it possible to apply a generic light recipe, which emerges, for example, from the ideal conditions of growing and/or breeding plants, to a light fixture, the properties of which (type and number of light sources) are not known in advance. Here, the generic light recipe may be present only in the form of intensity over wavelength (or wavenumber), either continuously or as discrete values for certain wavelength ranges. This would correspond to a light recipe for a light fixture, in which the number of different LED colors corresponds to the number of wavelength ranges in which the spectrum was stored. Thus, method 3 would be applied here.
4 th aspect of “Spectrum Calculation”: The controlled agricultural system as described in any one of the preceding aspects,
wherein the light sources of the light fixtures comprise LEDs.
5 th aspect of “Spectrum Calculation”: An agricultural method, comprising:
a light recipe for a first light fixture (first light-fixture-specific light recipe), a controlled agricultural system comprising a second light fixture that differs from the first light fixture, and the following method step: transforming the light recipe for the first light fixture into a light recipe for the second light fixture (second light-fixture-specific light recipe).
6 th aspect of “Spectrum Calculation”: The agricultural method as described in the 5 th aspect of “Spectrum Calculation”, wherein the transformation includes one or more of the following method steps:
selecting suitable light sources from the light sources available in the second light fixture, establishing the required spectral-range-specific light intensities of the respective light sources, establishing the required control signals for the respective light sources, applying the control signals to the respective light sources.
The above-described methods are also applicable to an arrangement of a plurality of light fixtures.
Finally, provision can also be made for the computer device to notify the user if a light recipe cannot be reproduced within a tolerance range by way of a light fixture. Additionally, there beyond, provision can also be made for the computing device to provide the user with propositions for a suitable modification of the existing light fixture, for example by complementing it with further light sources, or for a suitable new light fixture.
“Extended Recipes”
The present disclosure relates to a Controlled Agricultural System, an Agricultural Light Fixture for use in a Controlled Agricultural System and a Method for Agricultural Management.
Light recipes specify the spectrum, the light intensity (i.e. photon flux) and how long and at what times a specific light recipe is to be applied to a plant species. Usually, all relevant parameters are converted into respective currents or current modifying settings like PWM modulation, On/Off cycles and the like, which drive the light sources of a horticultural light fixture such that the light emitted by the horticultural light fixture reproduces the specific, desired, light recipe as good as possible.
High light intensities of light fixtures (brightness/luminance) typically require high driver currents causing high energy consumption. This may raise economical issues due to ever increasing energy costs as well as ecological concerns.
However, providing the intensity of the illumination (illuminance; or more plant specific: photosynthetic photon flux density [PPFD]) currently required by the light recipe may also be achieved in another manner, especially by bringing the horticultural light fixtures closer to the plants and/or by adjusting or modifying optical devices of the light fixtures, for example so that the illumination is more focused on parts of the cultivated area, on the plants or even on parts of the plants.
1 st aspect of “Extended Recipes”: A Controlled Agricultural System, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, particularly a plant growing facility and/or an aquaponics facility, comprising:
An agricultural light fixture arranged above an area cultivated with plants for illuminating the plants, An actuator device configured to be able to control the position/alignment of the agricultural light fixture, A computing device configured to control the brightness of the agricultural light fixture and to control the actuator device in order to effectuate an intensity of the illumination (illuminance) on the plants or parts of the plants according to a light recipe for the plants.
It is an advantage of “Extended Recipes” to safe energy by reducing the standard current setting (i.e. brightness) of a horticultural light fixture normally required according to the light recipe, and still keeping the illumination on the plants compliant to the light recipe. This is achieved by adjusting and/or modifying a horticultural light fixture, for example, by bringing the light fixture closer to the plants, according to the light recipe.
Therefore, “Extended Recipes” proposes a controlled agricultural system, comprising an agricultural light fixture, which agricultural system is configured to be able to control the position and/or orientation and/or shape of the agricultural light fixture with respect to the plants and/or adapt an optical device, arranged downstream of the light sources of the agricultural light fixture, according to the light recipe.
For this purpose, the controlled agricultural system further comprises a computing device and a data storage device. The data storage device comprises the respective light recipe for the plant species. The computing device is configured to be able to access the data of the light recipe (i.e. current light spectrum, intensity and duration of exposure to light irradiation) from a data storage device.
2 nd aspect of “Extended Recipes”: The Controlled Agricultural System according to the 1 st aspect of “Extended Recipes”, wherein
the actuator device comprises means for lowering or raising or aligning or moving or bending the agricultural light fixture with respect to the cultivated area.
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Furthermore, the computing device is configured to be able to compute a position/alignment of the agricultural light fixture that results in a higher light intensity as originally prescribed according to the light recipe. Particularly, the agricultural light fixture may be moved closer to the plants. Moving closer may be accomplished by moving the agricultural light fixture vertically closer, i.e. reducing the distance above the plants, and/or laterally closer, i.e. reducing the distance at the side of a respective plant. Concurrently, the current for the light sources, e.g. LEDs, may be reduced, compared to the current setting originally necessary, such that the resulting light intensity illuminating the plants in the target area matches with the light intensity according to the light recipe, while at the same time using less energy to realize the intended illumination target value.
3 rd aspect of “Extended Recipes”: A Controlled Agricultural System, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, particularly a plant growing facility and/or an aquaponics facility, comprising:
An agricultural lighting fixture arranged above an area cultivated with plants for illuminating the plants, comprising an optical device for adjusting the intensity of the light emitted by the agricultural lighting fixture during illumination, An actuator device configured to be able to control the optical device of the agricultural light fixture, A computing device configured to control the brightness of the agricultural light fixture and to control the actuator device in order to achieve an intensity of the illumination (illuminance) on the plants or parts of the plants according to a light recipe for the plants.
The optical device of the agricultural light fixture may be adjusted to focus the illumination more on the plants, for example by narrowing or widening the beam angle/spread. Furthermore, depending on the size of the plants, it may be necessary to adjust the optical device such that after moving the agricultural light fixture closer to the plants the illuminated area is still sufficiently large. The computed new position and/or shape of the agricultural light fixture and—as the case may be of the optical device—is sent by the computing device to a control unit, which controls the agricultural light fixture and/or optical device correspondingly.
The optical device may be adjusted by moving lenses of a lens system or by using an adaptable lens, the focal length of which can be adjusted by changing the curvature of the surface of the lens. Alternatively, reflective optical means may be used to adjust the focusing properties of the optical device.
4 th aspect of “Extended Recipes”: The Controlled Agricultural System according to the 3 rd aspect of “Extended Recipes”, wherein
the optical device comprises one or more of the following:
A lens with adaptable focal length (e.g. by adjusting the curvature of the lens), a lens system, comprising two lenses, which are movable with respect to one another, a reflector.
5 th aspect of “Extended Recipes”: The Controlled Agricultural System according to any one of the preceding aspects, further comprising
a data storage device connected to the computing device, the data storage device comprising a light recipe for the plant to be illuminated.
The data storage device may furthermore contain information on how mechanical changes of the position/alignment of the agricultural light fixture or the optical device of the agricultural light fixture influence the illumination, i.e. the photon flux at the plants. Thus, it is possible to calculate the feasible reduction of brightness of the light sources and, therefore, of the current setting for the light sources achieving a lower power consumption, due to mechanical changes of the position/alignment/shape of the agricultural light fixture and/or its optical device (or vice versa), and still being compliant with the light recipe.
6 th aspect of “Extended Recipes”: The Controlled Agricultural System according to the 5 th aspect of “Extended Recipes”, wherein the light recipe further comprises parameters that control supplemental functions in an agricultural facility (extended light recipe).
Thus, besides changing the mechanical or optical properties of the agricultural light fixture, further parameters of the agricultural facility (e.g. greenhouse, vertical farm) may be adjusted in order to meet the requirements of the light recipe. For instance, the temperature inside the agricultural facility may be adjusted, because the temperature influences the growth rate at a predefined light intensity
Furthermore, the light recipes may comprise parameters that control supplemental functions in the agricultural facility (extended light recipe). For instance, the extended light recipes may comprise parameters that specify the proper adjustment of the position of the agricultural light fixture or of its optical device without the need of computing such parameters from the light intensity data.
7 th aspect of “Extended Recipes”: The Controlled Agricultural System according to the 6 th aspect of “Extended Recipes”, wherein the extended light recipe comprises parameters that specify the proper adjustment of the position/alignment of the agricultural light fixture or of its optical device.
8 th aspect of “Extended Recipes”: The Controlled Agricultural System according to the 6 th or 7 th aspect of “Extended Recipes”, wherein the extended light recipe further comprises parameters that control any one of the following: polarization, collimation or coherence of the light emitted by the agricultural light fixture, environmental temperature, humidity.
To summarize, the light recipes may comprise parameters that control any one of the following: polarization, collimation or coherence of light, environmental temperature, humidity. A light recipe may further comprise adaptive irradiation settings as a function of plant growth, shape and fruition. Therefore, distance, inclination, adjustment of optical part can be regulated depending on irradiation time or measured plant growth/shape and the like.
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9 th aspect of “Extended Recipes”: The Controlled Agricultural System according to any one of the 6 th to 8 th aspect of “Extended Recipes”, wherein the actuator device is further configured to be able to control the supplemental functions.
10 th aspect of “Extended Recipes”: A method for agricultural management, particularly for breeding, growing, cultivating and harvesting plants arranged in a cultivated area in an agricultural facility, e.g. a plant growing facility, comprising:
A light recipe and an agricultural light fixture for illuminating plants, and the steps of:
Illuminating plants with the agricultural light fixture according to the light recipe; Decreasing the distance between the agricultural light fixture and the plants by lowering the horticultural light fixture down closer to the plants, while reducing the brightness of the agricultural light fixture to keep the illumination on the plants specified by the light recipe constant.
11 th aspect of “Extended Recipes”: A method for agricultural management, particularly for breeding, growing, cultivating and harvesting plants arranged in a cultivated area in an agricultural facility, e.g. a plant growing facility, comprising:
A light recipe and an agricultural light fixture for illuminating plants, whereby the agricultural light fixture comprises an optical device configured to be able to focus the illumination on parts of the cultivated area and/or on parts of the plants, and the steps of:
Illuminating plants with the agricultural light fixture according to the light recipe; Adjusting the optical device to focus the illumination more, e.g. on parts of the cultivated area, on the plants and/or on parts of the plants, while reducing the brightness of the agricultural light fixture to keep the illumination on the plants specified by the light recipe constant.
12 th aspect of “Extended Recipes”: The method for agricultural management according to the 10 th and/or 11 th aspect of “Extended Recipes”, for controlling a Controlled Agricultural System according to any one of aspects 1-9.
13 th aspect of “Extended Recipes”: A computer program product, comprising:
a plurality of program instructions, which when executed by a computer system of a Controlled Agricultural System according to any one of the 1 st to 9 th aspect of “Extended Recipes”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 10 th to 12 th aspect of “Extended Recipes”.
“Light Recipe & VLC”
1 st aspect of “Light Recipe & VLC”: A Controlled Agricultural System comprising
a first light fixture with a light source for agricultural lighting, wherein the Controlled Agricultural System is configured for modulating an emission of the light source to transmit data via this modulated signal.
The modulation can for instance be achieved by modulating the intensity, for instance by superimposing an intensity change or by switching off the light source for short intervals. The modulation can also be achieved by a pulse modulation, for example a Pulse Width Modulation (PWM), a Pulse Frequency Modulation, a Pulse Code Modulation or a Pulse Phase Modulation. The modulated signal can be received by a photodiode, and the data contained in the signal is available after a demodulation.
Accordingly, the lighting appliance of the agricultural system or farm can be used for transmitting data to other appliances, for instance control data to trigger actuators, for example for irrigation, manuring, heating/ventilation or the like, or to trigger a transportation of plant boxes from one lighting station to the next, or to trigger bendable or moveable fixtures to change their form, position or inclination. Using the light source intended for the agricultural lighting also for the data transmission can reduce the overall number of components and the complexity of the system, too. For instance, the wiring effort can be reduced.
2 nd aspect of “Light Recipe & VLC”: The Controlled Agricultural System of the 1 st aspect of “Light Recipe & VLC”, comprising a second light fixture configured for receiving the modulated signal and thus the data from the first light source.
In some embodiments/implementations, the controlled agricultural system is configured for transmitting lighting parameters via the modulated signal from the first light fixture as a master to the second light fixture as a slave, but a mesh configuration can also be possible. A computing device can be connected to the first light fixture, for instance directly or via a light control unit. The connection between these components can be wireless or wire based, combinations are possible as well. Upon receiving the lighting parameters from the computing device or the light control unit, the first light fixture can emit the modulated signal for transmitting these lighting parameters to the other light fixtures. The computing device or the light control unit can be an integral part of a lighting fixture. This transmission can happen immediately upon receiving the lighting parameters from the computing device, but also after a predefined or stochastic time interval. Such a data set can contain a fixture identifier so that just the related (second) fixture responds to that data set, supposed second fixture has such an (electronic, software code) identifier and respective detection units.
3 rd aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to the 1 st or 2 nd aspect of “Light Recipe & VLC”, comprising a computing device connected to the first light fixture, the Controlled Agricultural System being configured for transmitting lighting parameters via the modulated signal from the first light fixture as a master to the second light fixture as a slave.
Upon receiving the lighting parameters from the first light fixture, the emission of the second light fixture can be adapted respectively. In particular, a light control unit of the second light fixture can amend the emission as required. This light control unit is connected to the second light fixture, and is connected to a sensor device (e.g. a photodiode) for receiving the modulated signal or comprises such a sensor device as an integral part.
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The master/slave architecture can be advantageous in terms of a flexible setup of the agricultural system or farm. For instance, in case that additional lighting fixtures are required for an extension of the farm, those can be installed as slaves. Likewise, the lighting of a large number of light fixtures can be aligned and/or synchronized rather automatically. Advantageously, if required, an additional light fixture can be put in place and receives the lighting parameters to be applied, a connection to the power supply being the only installation necessary. Agricultural lighting fixtures can build up a network that may comprise sub-networks, that is, grouped fixtures that can be addressed with the same data set command.
4 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to the 3 rd aspect of “Light Recipe & VLC”, comprising a further light fixture, wherein the Controlled Agricultural System is configured for modulating an emission of a light source of the second light fixture for transmitting the lighting parameters from the second light fixture to the further light fixture as a slave.
In general, but also in the master/slave setup, also the second light fixture can be adapted for a modulated emission and for transmitting data via this modulated signal to a third fixture and/or back to the first fixture and/or to any other agricultural device (as described above). This also enables a feedback loop. The second light fixture can for instance transmit growth data of the plants illuminated or other local parameters to the first light fixture (and the computing device thus). On the other hand, the second light fixture can be used as an amplifier or distributor, namely for transmitting the lighting parameters to further light fixtures arranged at a larger distance from the first light fixture. In particular, this enables a transmission of the lighting parameters from the first light fixture (master) to light fixtures provided as slaves, even when the latter are not illuminated by the first light fixture directly, thus enabling a data distribution network.
In general, the spectral composition of the emitted light could be adaptively adjusted or fixed. Then, the lighting parameters can for instance be intensity values. Preferably, the light fixtures are adapted for an illumination with different spectral properties (with different light source types, see below) so that the lighting parameters are also spectral parameters (in addition to intensities). Spectral parameters can include other optical data, for example the polarization of the emitted spectrum.
Basically, the light emitted by a light fixture for agricultural lighting can be monochromatic light (FWHM <25 nm, or case of a laser light source <5 nm) or narrow band radiation (FWHM <50 nm) or broadband radiation (FWHM >100 nm) or a mixture thereof. The term “light” shall comprise spectral ranges outside the visible light spectrum. Respective non-visible spectral ranges can be infrared and/or UV.
5 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects, comprising an actuator device for providing at least one of irrigation, manuring, heating, ventilation and air conditioning to plants grown in the Controlled Agricultural System, the Controlled Agricultural System being configured to trigger the actuator device by the modulated signal emitted by the first light source.
This can be an alternative or a supplementation to the communication amongst the light fixtures. The actuator device can be a robot or vehicle, in particular a self-driving vehicle, but also a stationary appliance. The actuator device can comprise a sensor device, in some embodiments/implementations a photoelectrical sensor, for receiving the modulated signal. The modulated signal can be received by the actuator device directly or by an external receiving unit connected to the actuator device via an interface.
In some embodiments/implementations, the actuator device is adapted for providing irrigation, manuring, heating, ventilation and/or air conditioning to the plants grown in the farm or to trigger a transportation of plant boxes from one lighting station to the next, or to trigger bendable or moveable fixtures to change their form, position or inclination. Via the modulated signal, the actuator device can be triggered to adjust at least one of the respective conditions, for instance based on a light recipe applied.
6 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to the 5 th aspect of “Light Recipe & VLC” in combination with the 3 rd or 4 th aspect of “Light Recipe & VLC”, the Controlled Agricultural System being configured for transmitting based on a growth status of plants grown in the Controlled Agricultural System a light recipe, namely various lighting parameters via the first light fixture to the second light fixture or fixtures and various actuation parameters to the actuator device.
A “light recipe” can define lighting conditions. It can contain information and executable commands that control the light intensity and/or wavelength/spectral composition. A light recipe can be adaptive, namely depend on external trigger signals or feedback loops, particularly depending on the growth status of the plants. In other words, a light recipe contains a data set that provides for every point in time operational data to enable a lighting fixture to emit the required spectral composition and spectral intensities.
In some embodiments/implementations, the modulation of the signal is used for transmitting a light recipe via the modulated signal. In particular, the first light fixture can be used for transmitting lighting parameters to second light fixtures and actuation parameters to the actuator device, both based on the growth status of the plants.
7 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, wherein the first light fixture comprises light sources of different types with different spectral properties, a control unit for modulating the emission being configured to modulate the emission of the different light source types in at least in one mode of operation simultaneously.
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Thus, the light fixture(s) comprise(s) light sources of different types. The different types differ in their spectral properties (e. g. green, red, far red and so on).
In some embodiments/implementations, a control unit for modulating the emission is configured to modulate the different light source types simultaneously, at least in one mode of operation. For instance, the green, red and far red light sources can be modulated simultaneously. In some embodiments/implementations, in this mode of operation, all light source types are modulated. In other words, the whole electromagnetic spectrum of the first light fixture is modulated, the data being contained at every wavelength of the spectrum. The control unit for modulating the emission can be a separate device provided between a computing device and the light fixture. However, it can also be an integral part or function, for instance of the computing device or the light control unit.
8 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, wherein the first light fixture comprises light sources of different types with different spectral properties, a control unit for modulating the emission being configured to leave the emission of at least one light source type unmodulated in at least in one mode of operation while the emission of at least one other light source type is modulated.
The modulation is applied selectively in an interval of the light fixture's spectrum. For instance, only one light source type (e.g. green) can be modulated while the other light source types are not modulated. A modulation in groups is also possible, so that for instance green and yellow are modulated while red is not modulated, or vice versa. It is also possible to switch the modulation from one colour to another in a predetermined way but also in a freely selectable manner including a stochastic switch between various colours.
9 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, wherein the first light fixture comprises light sources of different types with different spectral properties, the Controlled Agricultural System being configured for applying a light recipe, namely various lighting parameters depending on a growth status of plants grown in the Controlled Agricultural System, and wherein a control unit for modulating the emission is configured to modulate different light source types based on the light recipe.
In a preferred embodiment, the control unit for modulating the emission is configured to modulate different light source types based on the light recipe. Thus, the modulation and communication depend on the light selected for the illumination. When the latter changes according to the light recipe, another light source type or other types are chosen for the modulation. The communication switches to a different colour. In case that more than one light source type is used for the lighting, the one having the highest intensity can be chosen for instance.
10 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, wherein the first light fixture comprises light sources of different types with different spectral properties, a control unit for modulating the emission being configured to modulate the light source types differently in a last one mode of operation, different data being transmitted via the different light source types.
Accordingly, having different light source types at hand is used for a multichannel communication. For instance, one light source type and spectral range can be used for transmitting lighting parameters to the other light fixtures. Another light source type and spectral range can be used for transmitting actuation parameters to an actuator device. Accordingly, the respective data transmitted via the respective light source type can contain only the information necessary for the devices of the respective channel. This allows reducing the losses resulting from the modulation in terms of the lighting of the plants.
11 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, configured for monitoring a reduced lighting of plants grown in the Controlled Agricultural System, which results from the modulated emission.
For instance, the total or a wavelength-specific photon flux can be measured. In some embodiments/implementations, the off-time or reduced emission time is derived directly from the control unit for modulating the emission.
In some embodiments/implementations, a countermeasure for compensating the reduced emission is taken, depending on a threshold value for instance, the light recipe can be modified, particularly the intensity can be increased. Alternatively or in addition, the overall duration of the lighting can be increased, and/or the distance between a lighting fixture and the irradiated plant can be reduced and/or the orientation of a fixture can be adjusted.
12 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to the 11 th aspect of “Light Recipe & VLC”, configured for compensating the reduced lighting by adjusting at least one of a light recipe, an overall intensity and an overall duration of the lighting.
13 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to one of the preceding aspects of “Light Recipe & VLC”, the first light fixture comprising light sources of different types, wherein the emission of at least one light source type lies outside the visible spectral range, and wherein a control unit for modulating the emission is configured to modulate at least in one mode of operation the at least one light source type outside the visible spectral range.
The light source type having an emission outside the visible spectral range, for instance an UV or IR light source. In some embodiments/implementations, the emission of this light source type is modulated in at least one mode of operation so that the non-visible light is used for transmitting data.
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14 th aspect of “Light Recipe & VLC”: The Controlled Agricultural System according to the 11 th and 13 th aspect of “Light Recipe & VLC”, optionally in combination with the 12 th aspect of “Light Recipe & VLC”, configured for compensating the reduced lighting by switching into the at least one mode of operation in which the at least one light source type outside the visible spectral range is modulated.
Thus, the non-visible spectral region is modulated when the aforementioned losses in the visible spectral range become too large.
15 th aspect of “Light Recipe & VLC”: A Method for Controlling a Controlled Agricultural System according to one of the preceding aspects, wherein an emission of the light source is modulated to transmit data via this modulated signal.
16 th aspect of “Light Recipe & VLC”: A Computer program product, comprising:
a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 14 th aspect of “Light Recipe & VLC”, cause the Controlled Agricultural System to execute the Method of the 15 th aspect of “Light Recipe & VLC”.
“Temperature Control”
“Temperature Control” proposes a method of how temperature conditions can be changed or adjusted to counter-influence (negative), keep or enhance (positive) Plant Growth or plant Time-to-Harvest conditions affected by the local temperature (or integral local temperature) settings at the location of a plant.
Temperature control units for agricultural facilities like horticulture farms, vertical farms or greenhouses usually try to keep the temperature at a certain, constant level. If the temperature rises above the level (e.g. in greenhouses on a very sunny day), measures are taken to reduce the temperature (e.g. open the windows to create air ventilation, or start a cold liquid irrigation system). If the temperature rises below a certain level, a heating device is switched on to restore the target temperature in the agricultural facility.
Horticultural lighting fixtures produce an enormous amount of heat. For example, the control systems of vertical farms may try to keep a constant (vertical) temperature in the building. However, due to the large number of illuminations units and other electrical equipment, which produce heat, and the large dimensions of typical vertical farms, it is unavoidable, that the temperature under the ceiling is higher than on the ground (as warm air is lighter and moves up [natural heat convection]). Therefore, the temperature conditions in soil and air (and possibly also the water irrigation temperature) is different at different height levels.
Temperature, however, has an influence on the growth of plants. Some plants like petunia or verbena need less time to flowering the higher the temperature is. However, petunia grow faster the higher the temperature is, whereas verbena grow faster the lower the temperature is. Other plants like salvia have a maximum growth rate at about 22° C., whereas they grow slower for higher and lower temperatures.
Example Petunia Coral Pink
The following shows the respective time to flower (days) at four different temperatures (14, 17, 20, 23 [° C.]) and four different DLI (daily light integral) values (5, 10, 15, 20 [mol/m 2 d]):
Time to flower at 14° C.: at 5 mol*m−2*d−1: more than 80 days Time to flower at 17° C.: at 5 mol*m−2*d−1: ca. 48 days Time to flower at 20° C.: at 5 mol*m−2*d−1: ca. 35 days Time to flower at 23° C.: at 5 mol*m−2*d−1: ca. 30 days Time to flower at 14° C.: at 10 mol*m−2*d−1: ca. 65 days Time to flower at 17° C.: at 10 mol*m−2*d−1: ca. 40 days Time to flower at 20° C.: at 10 mol*m−2*d−1: ca. 30 days Time to flower at 23° C.: at 10 mol*m−2*d−1: ca. 28 days Time to flower at 14° C.: at 15 mol*m−2*d−1: ca. 50 days Time to flower at 17° C.: at 15 mol*m−2*d−1: ca. 35 days Time to flower at 20° C.: at 15 mol*m−2*d−1: ca. 28 days Time to flower at 23° C.: at 15 mol*m−2*d−1: ca. 23 days Time to flower at 14° C.: at 20 mol*m−2*d−1: ca. 42 days Time to flower at 17° C.: at 20 mol*m−2*d−1: ca. 30 days Time to flower at 20° C.: at 20 mol*m−2*d−1: ca. 25 days Time to flower at 23° C.: at 20 mol*m−2*d−1: ca. 20 days
These examples illustrate how the temperature influences the growth, particularly the time to flower.
Plants, however, do not only require a stable temperature, they also require certain, regular changes in temperature. For example, the circadian clock of plants is sensitive to temperature. Many processes of the plant are controlled by the circadian clock. Some other plants, for example, require low temperature to be able to complete their development cycle. This phenomenon is known as vernalization and can imply weeks at low temperature, typically between 5 and 10° C., for a plant to be able to flower.
To improve the yield and the quality of plants in an agricultural facility, it is thus necessary to provide an agricultural system, which sets the temperature of the agricultural facility in a controlled way. The controlled way does not target a stable temperature over the whole time until harvest, but it targets regular temperature modifications or changes in a proper and consistent manner.
1 st aspect of “Temperature Control”: A controlled agricultural system, particularly for plant breeding, growing, cultivating and harvesting in an agricultural facility, comprising:
a sensor device, comprising temperature measuring means able to measure the (local) temperature, in some embodiments/implementations at various locations, in the agricultural facility, an actuator device, comprising temperature influencing means able to influence/change the temperature in the agricultural facility, a data storage device for storing growth settings for plants, the growth settings comprising temperature profiles (temporal and/or spatial), a computing device, configured to fetch a growth setting for a respective plant species from the data storage device, the computing device, further configured to adjust the temperature in the agricultural facility according to the temperature profile of the growth setting by means of the sensor device and the actuator device.
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The computing device may contain the growth settings, e.g. in a database (local, remote or cloud), for a specific plant. These settings can be fix (preset/default). Furthermore, the computing device may also have an interface so that the user can choose the respective plant and the computing device picks the required growth settings, or the user can pick the growth settings directly via the interface. The growth settings can be different for each plant species.
Temperature adjustments can be conducted in a smooth way (low change gradient) or at a higher pace or in discontinues ways (jumps).
The growth settings comprise a temperature profile over time (temporal temperature profile). This temporal temperature profile can be defined to support the circadian rhythm of the plant, i.e. it repeats itself after a certain time (e.g. 24 hours). A temperature profile may include higher temperatures during the daytime and lower temperatures during the nighttime of the plant (as plants can be grown in vertical farms, the daytime of the plant can be night time outside, as electrical power is cheaper during the night).
This allows supporting the circadian rhythm of the plant. Of course, the time shift between the temperature profile and the natural circadian cycle can be freely adjusted. It is also possible, to set the ‘artificial circadian’ cycle to longer values than the ones for the (local) natural circadian cycle, or even to multiples of the natural circadian cycle. Also, the duration (hours) of ‘day’ vs. ‘night’ can be freely adjusted.
The temperature profile can also have different settings for different growth phases of the plants like germination, growing, flowering etc. Here the overall temperature profile for one growth phase can have higher or lower average temperatures as for another growth phase of the plant. Furthermore, the daily difference between maximum and minimum temperature as well as the absolute values of the temperature profile can be different for different growth phases of the plants.
It is of course also possible, to locally set or adjust the temperature settings (spatial temperature profile), e.g. in the soil and at the plant top, differently, i.e. to keep or change a temperature gradient across the height of a plant (vertical temperature profile).
2 nd aspect of “Temperature Control”: The Controlled Agricultural System according to the 1 st aspect of “Temperature Control”, wherein the temperature influencing means are configured to influence the temperature differently in different locations of the agricultural facility.
3 rd aspect of “Temperature Control”: The Controlled Agricultural System according to the 1 st or 2 nd aspect of “Temperature Control”, wherein the computing device is further configured to keep or change a vertical temperature profile across the height of the agricultural facility or of plants.
The controlled agricultural system can further comprise an actuator for influencing/changing/adjusting/controlling the temperature (temperature influencing means), i.e. a heating and cooling system like an HVAC (heating, ventilation and air conditioning), a heating pipe, IR (infrared)-radiator, etc. In a vertical farm setting, the temperature influencing means can be different at different height levels, e.g. irrigation, cool airflow, wind channels, heat shields. Heat can also be applied by irradiating the plants with Infrared radiation in the wavelength range between 850 and 4000 nm, or longer. Local heating can be applied by using e.g. a moveable infrared laser device that emits IR-radiation on selected plants or selected groups of plants, or at a certain position on the plant (root, buds, petals, etc.). Cooling airflow can be applied through ducts along the plants or by focused jet streams.
4 th aspect of “Temperature Control”: The Controlled Agricultural System according to any one of the preceding aspects, wherein the temperature influencing means of the actuator device are moveable and/or mobile.
5 th aspect of “Temperature Control”: The Controlled Agricultural System according to any one of the preceding aspects, wherein the temperature influencing means of the actuator device comprise one or more of the following means: heating device, cooling device, HVAC, heating pipe, IR-radiator, irrigation, cool/warm airflow, wind channel, heat shields.
Furthermore, the controlled agricultural system comprises temperature sensors that are used to measure the temperature and provide the information to the computing device. Based on this information, the computing device determines the difference between actual and target values and initiates a respective heating or cooling of the agricultural facility. The sensors and actuators may be controlled by respective control units.
The controlled agricultural system may also comprise sensors to detect ambient lighting, or other ambient environmental conditions such as CO 2 -content in the air. This may be used to align or correlate the temperature-initiated circadian rhythm with the light-induced circadian rhythm of the plants. Additional sensors and actuators may be used to monitor and adjust (within meaningful ranges/boundaries) other correlations, e.g. between temperature settings and the Daily Light Integral (DLI) or the Red/Far-Red Photon Flux Ratio, or the amount of applied fertilizers or pesticides. Furthermore, temperature conditions can be changed as a function of energy prices.
6 th aspect of “Temperature Control”: The Controlled Agricultural System according to any one of the preceding aspects of “Temperature Control”, wherein the sensor device further comprises one or more sensors able to detect the growth status (shape, size, color, etc.) of the plants, e.g. imaging devices like cameras.
Thus, the controlled agricultural system may also comprise sensors to detect the growth state of the plants, e.g. cameras, including thermal and hyperspectral cameras. If a certain growth state is detected, the computing device may switch the growth settings accordingly.
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In another embodiment of “Temperature Control”, the computing device has an internal clock (or is connected to an external clock) and determines only based on the time passed and the kind of plant (species) when a new growth state of the plant will begin.
7 th aspect of “Temperature Control”: The Controlled Agricultural System according to the 6 th aspect of “Temperature Control”, wherein the computing device is further configured to determine the growth phase (e.g. breeding, greening, flowering and harvest) of the plants based on the data from the sensor device.
Proper research can measure and assess the necessary temperature levels in order to reach the desired plant growth values, like Time to Flower. Such relations can be done with all plants (or at least with a relevant subset) and stored into a database. The database then allows producers to adjust the temperature levels (increase, keep, decrease) appropriately in order to influence plant growth, flowering or harvesting parameters. In a preferred embodiment, such a database is stored in a data storage device connected to the computing device of the controlled agricultural system.
In other words, proper research can measure plant growth, plant morphology, plant chemistry, plant leaf density index, plant color and other growth and ripening indicative parameters with various measurement techniques (destructive and non-destructive) at certain temperatures. These data may then be stored into the database bank (Growth Parameters GP).
8 th aspect of “Temperature Control”: The Controlled Agricultural System according to any one of the preceding aspects of “Temperature Control”, wherein the computing device is further configured to fetch a growth setting including a temperature profile dedicated to the present growth phase of the plants from the data storage device.
The controlled agricultural system may further comprise an illumination system coupled to the computing device. The illumination system may be illuminated using a light recipe, which may also be stored in the computing device (if the computing units comprises a data storage device) or in a separate data storage device connected to the computing device. The computing device assures that the growth settings containing the temperature profile and the light recipe are aligned to each other (synchronized), i.e. the “morning state” of the grow setting is also the “morning state” of the light recipe (the same for midday, evening or settings in between).
In another embodiment, the growth setting and the light recipe are provided as one dataset, so that no additional alignment is necessary.
9 th aspect of “Temperature Control”: A method for agricultural management, particularly for plant breeding, growing, cultivating and harvesting in an agricultural facility, comprising:
at least one controlled agricultural system according to one or more of the 1 st to 8 th aspect of “Temperature Control”, and the steps of
Picking from the data storage device a growth setting including the correlated (temporal and/or spatial) temperature profile by means of the computing device,
Measuring the temperature in the agricultural facility by means of the sensor device (temperature sensors); Checking whether the measured temperature matches with the nominal value according to the selected temperature profile;
In case of mismatch between measured and nominal temperature: Changing the temperature according to the temperature profile by means of the actuator device 111 (temperature influencing means).
10 th aspect of “Temperature Control”: The method for agricultural management according to the 7 th aspect of “Temperature Control”, further comprising the initial step of
Choosing a plant species by the user via the user interface.
11 th aspect of “Temperature Control”: The method for agricultural management according to the 9 th or 10 th aspect of “Temperature Control”, further comprising the step of
Correlating the selected temperature profile with one or more of the following environmental/plant conditions: day-night-shift, circadian rhythm of the plant, illumination conditions, plant growth phase.
12 th aspect of “Temperature Control”: The method for agricultural management according to any one of the 9 th to 11 th aspect of “Temperature Control”, further comprising the step of
Synchronizing the temperature profile and the light recipe.
In an embodiment/implementation for saving energy, the temperature profile and the light recipe are synchronized to influence the plants in the same way, for instance, to speed up plant growth or delay plant growth (see e.g. the element “Flexible Growth”).
13 th aspect of “Temperature Control”: The method for agricultural management according to any one of the 9 th to 11 th aspect of “Temperature Control”, further comprising the step of
Detecting the growth status/phase of the plants by means of the sensor device.
14 th aspect of “Temperature Control”: The method for agricultural management according to the 13 th aspect of “Temperature Control”, further comprising the steps of
Comparing the presently detected growth data with the previously detected growth data or data stored in the database and checking by means of the computing device whether the growth phase (e.g. breeding, greening, flowering and harvest) has changed, If the growth phase has changed: Picking from the data storage device a growth setting including the (temporal and/or spatial) temperature profile correlated to the new growth phase by means of the computing device.
15 th aspect of “Temperature Control”: A computer program product, comprising:
a plurality of program instructions, which when executed by a computer system of a Controlled Agricultural System according to any one of the 1 st to 8 th aspect of “Temperature Control”, cause the Controlled Agricultural System to execute the method for Agricultural Management according to any one of the 9 th to 14 th aspect of “Temperature Control”.
16 th aspect of “Temperature Control”: Agricultural facility ((vertical) farm, greenhouse, etc.) with at least one Controlled Agricultural System according to any one of the 1 st to 8 th aspect of “Temperature Control”.
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Examples for Light/Growth Recipes
In practice, the selection of a growth or light recipe can depend on many factors. Below, some influencing parameters and boundary conditions are discussed for the purpose of illustration. Further, some exemplary recipes are shown.
Growth Phases
Requirements for optimized lighting conditions can for instance vary with the three distinctive growth phases, i.e.
a) Establishment growth: occurs after seed germination or while you are rooting and establishing vegetative
b) Vegetative growth: occurs when leaves and stems are rapidly growing
c) Reproductive growth occurs as plants transition to produce flowers and subsequent fruit
An initial goal for most crops can be to establish large leaves and stems to provide plants with enough photosynthetic area to produce carbohydrates that will be allocated to flowers and fruits during the reproduction phase. The allocation of photosynthates from ‘sources’ (active leaves) to ‘sinks’ (roots, shoots, flowers, and fruits) is an important balance influenced by environmental conditions.
The principle of limiting factors also relates to photosynthate allocation. Plants are highly adaptive, due to their inability to relocate to an ideal environment. If an environmental variable is not favorable, plants allocate energy resources to increase their chance for survival. For example, in nutrient-limited conditions, a plant will allocate resources to expand root growth, while in light-limited conditions, resources will be allocated to stem and leaf growth.
Light Saturation:
As light intensity (PPFD) increases, photosynthetic rates also increase until a saturation point is reached. Every plant species has a light saturation point where photosynthetic levels plateau. Light saturation normally occurs when some other factor (normally CO2) is limited.
Photoacclimation:
During establishment growth (a), light intensities need to be kept relatively low as the plant is developing roots, leaves, and stems that will be used to provide photosynthates during the vegetative growth phase (b). Increasing light intensity as you transition into the vegetative (b) and reproductive growth phases (c) will increase the rate of photosynthesis, which will provide the plant with more photosynthates used to develop flowers and subsequent fruit. Plants need time to acclimate to high light intensities (referred to as photoacclimation). If plants are exposed to high light intensities too early in the crop cycle, chlorophyll pigments can be damaged causing photo-oxidation (photo-bleaching). As a general rule, increasing by 50 μmol/m2/s or less per day, can be an appropriate approach.
Photoperiodism
Photoperiodism is a plant's response to the duration of the day (light period) in combination with the duration of the night (dark period). This phenomenon influences different plant responses such as flowering, vegetative reproduction and dormancy. Plants can be classified regarding their response to the daylength. The following are the current classes of photoperiod:
Short Day Plants (SDP) Long Day Plants (LDP) Day Length Neutral Plants (DLNP) Intermediate Day Length Plants (IDP) Dual Induction Plants (SLDP)
Daily Light Integral
The term daily light integral (DLI) is used to describe the total quantity of light delivered to a crop over the course of an entire day. The DLI is reported as the number of moles (particles of light) per day. Knowing the quantity of light delivered throughout the day can be a useful measurement for estimating the effect of sunlight on plant growth. Many important plant growth responses, such as biomass accumulation, stem diameter, branching, root growth and flower number are closely correlated to DLI. DLI can be a tool for managing the light environment to optimize plant growth.
Carbon Dioxide
Carbon dioxide (CO2) enrichment in a controlled agricultural environment can improve the yield of high PPFD crops. Typically, plants have a light saturation point where the maximum rate of photosynthesis is reached at a specific light intensity. However, at ambient atmospheric CO2 levels (˜400 ppm) it is the limited availability of CO2 that can restrict photosynthetic activity, not the intensity of light. Generally, optimum levels of CO2 will be two to four times the normal atmospheric levels (800-1,400 ppm CO2) when growing under high PPFD conditions. It may be recommended to supplement ≥800 ppm CO2 into a controlled agricultural environment when the plants are provided with ≥500 μmol/m2/s. When light intensity is increased, also CO2 levels can be increased as plants acclimate to increased PPFD.
Leaf Surface Temperature
Plant growth and development can also be influenced by temperatures at the growing points of plants (i.e., roots and shoot tips). It is rather plant temperature (not air temperature) that drives physiological responses in plants. Air temperature can differ by as much as 12° C. from plant temperature, depending on the used light source (e.g. High Pressure Sodium HPS, Metal-Halide MH, or LED), light intensity, humidity, and air speed. For example, HPS lights emit a large percentage of their energy in the infrared (IR) range (800 nm-1000 nm) which is not photosynthetically active yet significantly increases plant temperature, whereas suited LED-based systems produce very little radiant heat.
Photothermal Considerations
Crops can have a species-specific base temperature, at which growth and development will not occur. Above the base temperature, growth and developmental rates increase with temperature until an optimum temperature is reached. Above the optimum temperature, plant development decreases. Light intensity primarily influences the rate of photosynthesis, while plant temperature primarily influences developmental rates. Net photosynthesis under increased PPFD will increase as temperatures approach the optimum temperature for the species of grown plants; however, the optimum temperature for photosynthesis depends on the concentration of CO2 in the growth environment. An important correlation can be that with increased temperature, also the morphology of the plant will be changed by increasing developmental rates. The ratio between light intensity and temperature is known as the photothermal ratio. If one chooses to grow at warmer temperatures (≥80° F.), it can be necessary to ensure that an adequate light intensity (≥500 μmol/m2/s) is provided, otherwise plants could be produced that have increased internode distance, small stem caliper, and an overall spindly growth habit.
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Temperature Differential
The difference between day/night temperatures (DIF) can also influence plant morphology. For example, if day/night air temperature is 24/10° C., a +DIF of 12° C. results, which will promote stem elongation of most crops. Alternatively, a warmer night temperature 18/25° C. (day/night) will result in a −DIF of 12° C., which will suppress stem elongation.
Relative Humidity, Vapor Pressure Deficit, and Air Movement
Relative Humidity (RH) is the amount of humidity present at a given temperature and is expressed as a percentage. When air is completely saturated, it has a RH of 100%. Temperature, RH, and air movement can be three main variables that influence the movement of water throughout a plant. Evapotranspiration is the process plants use to cool leaf surfaces—as the temperature of a leaf increases, plants pull more water from the growing media and water is evaporated from the leaf surface, as a result, the leaf temperature decreases.
Vapor Pressure Deficit (VPD) can be a valuable tool to use when growing in a controlled environment. Maintaining a proper VPD will help to reduce plant stress brought on by either excessive transpiration (high VPD values) or the inability to transpire adequately (low VPD values). When the VPD is too low (humidity too high) plants are unable to evaporate enough water to enable the transport of mineral nutrients (such as calcium), and in cases where VPD is extremely low, water may condense on the plant surface and provide a medium for fungal growth and disease.
Air Movement
Proper Air Movement can also be an environmental variable that can be adjusted in controlled environment agriculture. Air flow can be critical to break the boundary layer around a leaf and allow transpiration and CO 2 uptake. It can also be beneficial to provide uniform temperature, humidity, and CO 2 concentrations in a controlled agricultural environment. Furthermore, an air flow against the plants will result in stronger growth of e.g. the stems. For instance, maintaining an air speed of 0.8-1.2 m/s at the plant canopy can optimize plant growth and development.
Exemplary Growth Recipes
Below, some exemplary growth recipes are shown. The first one relates to lettuce, in particular to improving red coloration of red leaf lettuce. The second one relates to basil. These two growth recipes are static, which means that the same growth conditions are applied over the whole growth cycle. The third growth recipe, which relates to Cannabis , is a dynamic recipe. For the flowering, the intensities given on the right are increased to a threefold value. In all recipes, the intensities are in indicated in μmol m −2 s −1 .
A further example of dynamic growth recipe is shown below. It relates to lettuce and shows three alternatives PPFD I-III.
A further example for influencing the plant properties by defined environmental conditions is a strengthening of the stem of flowers, for instance of petunia. A strengthening of the stem can for instance be achieved by illuminating the plants during the growth phase (after the formation of the first leaves until flower formation) with green light, e.g. with a wavelength between 500 nm and 550 nm and an intensity of at least 400 μmol m −2 s −1 .
Another example is an extension of the flowering, which can be achieved by an illumination with a wavelength between 400 nm and 800 nm, wherein the intensity between 450 nm and 500 nm amounts to more than 45% of the total intensity.
Luminaire
“Light Guides”
According to the element “Light Guides” of the disclosure, a light module comprising at least one light guide, which enables improved illumination of plants, is proposed. Furthermore, an agricultural lighting fixture comprising such a light module and a method for agricultural management providing improved illumination by means of the agricultural lighting fixture is proposed.
Below, various aspects and details of “Light Guides” are described.
1 st aspect of “Light Guides”: A light module, in particular for plants, comprising holding or fixation means and at least one light emitting element, wherein the light-emitting element is mountable to the holding means and wherein the light-emitting element comprises at least one light guide which is arranged in a pre-determined distance, in some embodiments/implementations in a common plane, to a target area.
Light Modules, Light Emitting Elements, Light Guides
According to an embodiment of “Light Guides”, a light module is provided, in particular for illuminating plants. The light module comprises holding or fixation means adapted to hold or fix the light module in place or fasten the light module to a supporting structure, such as a wall, a ceiling, a meshwork, a grid, beams or other structures. The holding means may also be provided to support parts of the light module. Separate holding means may also be provided, in order to hold or fix the light module and to support elements of the light module. The light module also comprises at least one light-emitting element. The light module and/or the light emitting element can comprise or include a transparent material. The light-emitting element of the light module comprises at least one light guide, which is arranged in a predetermined distance to the target area. The light guide, in particular an elongated light guide, can be arranged in a, usually horizontal, plane, with a predetermined distance to the target area.
The light guide can be placed such that it vertically extends downward, i.e. towards the plants or the target area. One or more light guides may be provided, which have portions arranged horizontally, i.e. forming a plane basically parallel to a target area and having portions arranged vertically, i.e. substantially normal to the target area or at least inclined with respect to the target area. However, multiple light guides may be provided wherein at least one of the light guides is arranged horizontally, and at least one, in some embodiments/implementations multiple, light guides are arranged vertically or at least inclined with respect to the target area.
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2 nd aspect of “Light Guides”: The light module according to the 1 st aspect of “Light Guides”, wherein the light-emitting element extends in different vertical layers, in some embodiments/implementations the layers forming planes and having a predetermined or adjustable distance to one another.
Providing light guides on different vertical layers or spanning different vertical layers, in particular between the plants, and controlling light parameters in a vertical direction, i.e. differently for different vertical layers, may improve illumination and light supply to the plants to be grown.
3 rd aspect of “Light Guides”: The light module according to the 2 nd aspect of “Light Guides”, wherein the at least one light guide is arranged in the at least two layers.
4 th aspect of “Light Guides”: The light module according to the 2 nd or 3 rd aspect of “Light Guides”, wherein the light-emitting element comprises multiple light guides, which are arranged in the at least one layer.
The light module according to the present disclosure may thus also be referred to as an adjustable inter-canopy light module, as it allows to adjust light parameters in different vertical layers even between plants.
5 th aspect of “Light Guides”: The light module according to the 4 th aspect of “Light Guides”, wherein the multiple light guides are controllable, in some embodiments/implementations separately, by a control unit.
According to an embodiment, a light guide may contain light sources (e.g. LEDs) that can be controlled individually or in groups. In particular, these light sources may be placed above or adjacent to each other along the longitudinal length of the light guide.
6 th aspect of “Light Guides”: The light module according to the 5 th aspect of “Light Guides”, wherein at least one light guide can be controlled to provide a different spectrum of light and/or a different light recipe compared to at least one other light guide.
The light sources may be individual LEDs or one or more groups of LEDs. These light sources may emit light of different spectral composition, thus allowing control and adjustment of the light spectrum emitted to the plants along a vertical direction.
In an embodiment, the light-emitting element or at least the light guide, may be placed with a uniform distance to the target area and, eventually, to the plants growing in the target area. In particular, this may also allow the light-emitting element or portions of the light-emitting element to be placed such that a uniform distance with respect to the plants may be adjusted, even if the size of the plants, in particular in a vertical direction, is not uniform. That way, the element “Light Guides” of the disclosure may allow vegetated areas and/or plants to be illuminated more evenly.
The use of light guides may allow the reduction of the distance of the light emitting element to the plants or target area, as they may provide more uniform illumination compared to point sources, such as single LED elements.
Further, according to an embodiment, the light module, or at least the light guide may be arranged in a horizontal way above the target area. A target area with this respect is an area, which is to be illuminated by the lighting fixture. It is understood that neither the lighting fixture, the light module, nor the light guide have to be arranged horizontally with respect to the target area, i.e. arranged in parallel to the target area, even if the lighting fixture, the light module, or the light guide may, at least in places, be arranged parallel to the target area.
According to another embodiment, the light-emitting element of the light module extends in different layers, wherein in some embodiments/implementations the layers are forming planes and in some embodiments/implementations are having a predetermined distance to one another. That way, the present disclosure may enable to further direct light to different regions of the plant, in particular to different vertical sections of the plant. Consequently, those leaves at the tip of the plants may be arranged between two layers of the lighting fixture, such that leaves and other plant sections below the uppermost leaves may be supplied with sufficient light. This may increase the agricultural outcome (yield). Those layers or parts of the layers being situated below the uppermost leaves may be controlled to emit light at a reduced or an increased intensity or with an altered spectrum of light, respectively a different light recipe. The light characteristics like photon flux quantity and/or photosynthetically active radiation (PAR) and/or light spectrum and/or operating conditions, for example the ON/OFF cycles of the provided illumination, and/or illumination phases with increased or reduced light intensity, e.g. boost and dim phases, may be changed over time as the plants grow and change their morphology.
According to an advantageous refinement, the at least one light guide of the light module is arranged in more than one of the layers forming the light-emitting element. In particular, the at least one light guide may be arranged in the at least two layers which can be stacked vertically on top of each other or, at least, in more than one of the layers. Alternatively, more than one light guide may be provided in the at least one or in more layers of the light module. This is to say that one or more light guides may be provided in one or more layers of the light module. A “layer” according to the element “Light Guides” of the disclosure means a portion of the light module that is adapted to illuminate a different section of the plant, in particular in a vertical direction, compared to another layer. Different layers may also be differentiated by their individual distance to the target area or any of the target areas.
As at least portions of the light guides may be provided along a vertical direction, vertical variation of emitted light spectra may be enabled by controlling light sources within a light guide. Such individual light sources being arranged in a light guide may thus form vertical layers as understood in the context of “Light Guides”.
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13 th aspect of “Light Guides”: The light module according to any one of the 1 st to 12 th aspects of “Light Guides”, wherein the at least one light-emitting element and/or the at least one light guide comprise or include fiberglass or plastic.
This may allow for better defining light guiding properties, amount and location of the out-coupling of light out of the light guide and other parameters. For instance, at predetermined positions, the light guide may be prepared to couple light out of the light guide. In particular, the light guide may comprise roughened portions, where the light can leave the light guide at such predetermined positions.
14 th aspect of “Light Guides”: The light module according to any one of the 1 st to 13 th aspects of “Light Guides”, wherein the at least one light guide comprises roughened portions adapted to guide light to predetermined positions.
It is also possible that the light guides are designed such that light with a predetermined wavelength or within a predetermined wavelength range may couple out of the fiber at one position, whereas light of different wavelength continues to travel within the light guide and may exit at another location. Thus, the “Light Guides” may enable to provide light in an advantageous manner compared to existing solutions.
While light guides commonly are perceived to be fiber-like structures, such as optical fibers, any design suitable for guiding light may be applied for light guides within the meaning of the “Light Guides”.
15 th aspect of “Light Guides”: The light module according to any one of the 1 st to 14 th aspects of “Light Guides”, wherein at least one light guide is a liquid light guide, in some embodiments/implementations adapted to guide light of the UV-part of the light spectrum.
In an advantageous refinement, the light guide may for instance be a liquid light guide. A liquid light guide within the perception of “Light Guides” refers to any kind of light guide, which, at least partially, uses a liquid medium as a light guide, to guide light of one or more wavelengths. Liquid light guides may be preferable in order to guide light comprising ultraviolet (UV) light. Thus, UV light may be guided to plants and even to predetermined sections of plants. Such light guides may be used e.g. in order to guide the light below the uppermost layer of leaves, i.e. the canopy. Thus, bottom sides of the plants and in particular of the leaves may be illuminated with light, e.g. UV light.
UV light may particularly be used to dispatch or control or minimize pests of various origins or fight at least some diseases (see also the element “Prophylaxis” of the disclosure). The light guides may also be provided in close proximity to or directly on the ground, i.e. the target area, in order to dispatch pests or vermin living on the ground. This may increase agricultural output and reduce crop failure. This again may allow enhancing predictability of the agricultural output and facilitate logistics before and after harvesting (see also the element “Yield Prediction” of the disclosure).
16 th aspect of “Light Guides”: The light module according to any one of the 1 st to 15 th aspects of “Light Guides”, wherein the light-emitting element comprises non-emitting portions and/or reflective portions and/or light conversion portions in order to emit light in the pre-determined direction.
In addition to or separately from the light guides, the light-emitting element may comprise sections with no or only minimal emission. For instance, the light-emitting element may comprise non-emitting portions and/or reflective portions, in order to emit light in a predetermined direction or to block it completely. Such non-emitting portions may be portions, within which the light guide is completely covered by a non-transparent and/or absorbing layer or is provided within a channel or the like. Reflective portions of the light-emitting element may be sections, where the light is coupled out of the light guide to one or more desired directions, whereas no emission takes place in other, non-desired directions. The reflective portions may in particular comprise a reflective layer provided on the light guide, in order to prevent light already from coupling out of the light guide. Further, the reflective portions may be provided such that light, which was emitted in a non-desired direction, will be incident on a reflective element to be reflected into a desired direction. A desired direction for instance would be toward a plant, a target area or the like. It is also within the framework of the aspect “Light Guides” to coat a light guide with a light conversion material or to implement such a light conversion material into a light guide, thus enabling a conversion of incoming wavelengths (excitation wavelength) into other ones, e.g. in the manner of down-conversion to longer wavelengths. By this, a light guide can provide different light spectra at different locations depending on the use of conversion materials and mix thereof.
17 th aspect of “Light Guides”: The light module according to any one of the 1 st to 16 th aspects of “Light Guides”, wherein the light-emitting element comprises a light source which comprises a semiconductor element, in some embodiments/implementations an LED or OLED element, in some embodiments/implementations a laser element.
The light-emitting element may in particular comprise one or more semiconductor elements as light sources. In some embodiments/implementations the light source may comprise or include a light emitting diode (LED) and/or an organic light emitting diode (OLED). The LEDs may be direct emitting diodes or so-called phosphor-converting diodes. In some embodiments/implementations, the light source may comprise or include a laser element. While, in some embodiments/implementations, the laser element is a semiconductor element, in some embodiments, the laser element may be based on non-semiconductor technologies. Such a laser element can also be used as part of a Laser Activated Remote Phosphor (LARP) conversion device. Combination of light guides with semiconductor light sources may allow simplified coupling of light into the light guide and delivery of the light to the region of interest, e.g. the plants, specific plant parts, the target area and the like.
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Advantageously, light originating from different light sources and/or of different wavelength may be combined in the light guides, in order to provide light with a pre-determined or desired spectral composition. Two or more light guides can be connected or combined into a single light guide, at least over a certain common length, and be separated again. Thus, different light guides can form a mesh of light emitting elements with similar or different lighting properties that can complement each other, for example with regard to locally emitted light intensity, spectrum, emission angle, angular beam spread, and operating modes. It is also within the framework of this disclosure that a light guide can be used as conducting means, for example by placing pipes or other transporting means inside a hollow light guide, to apply nutrients, fertilizer, irrigation and the like to the plants. A light guide can be made watertight so that it can also be used in aquaponics growth settings, e.g. as described for instance in the element “Aquaponics” of the group “System Setup” of the disclosure.
A light guide can have various cross sections and/or geometrical product dimensions along its axis or any other spatial extension. A light guide can emit different light recipes and use different light-changing or influencing means, as described above, along its circumference thus providing different lighting scenarios into different radiation angles, thus making it more versatile for plant illumination.
7 th aspect of “Light Guides”: The light module according to any one of the 1 st to 6 th aspect of “Light Guides”, wherein the at least one light guide comprises flexible material.
This allows directing the light along a definable, arbitrary path toward the target area or sections of the plants. This further allows mounting the light guide to supporting structures, such as a meshwork, which is distributed over the target area and in particular over the plants. The light guides may further be rotatable designed, in order to further individualize their respective emission scheme and alter or adapt the emission direction.
Control Unit and Lighting Parameters
Advantageously, the light guide or multiple light guides or different fractions of one or more light emitting elements or of the light module are controllable by means of a control unit. More advantageously, one or more light guides and/or light emitting elements are controllable separately from one another. With that respect, the control unit may be configured such that lighting parameters, such as wavelength, spectrum, spectral composition, light intensity, time of illumination or other parameters are controlled.
Further, the control unit may be enabled to, additionally or exclusively, control mechanical parameters of the light-emitting element and/or the light guide, such as the position relative to the target area, the plant to be illuminated, the holding means, or between different parts of the light module and/or the orientation thereof and/or the distance and angle between two or more light guides.
The control unit may also control light of at least one light guide or light-emitting element such that a different light recipe compared to at least one other light guide or light-emitting element is applied. This may allow providing the right illumination to the different parts of the plants, which, eventually, may increase the yield and quality of the agricultural output (agricultural produce).
A light recipe comprises information and control data of illumination with respect to time, location, light intensity, and other parameters suitable or necessary to control growth of the plants or phases of plant growth. A light recipe thus also includes dark phases, boost phases, dim phases and control of different spectra to be delivered to the plants. A light recipe may comprise control data for an entire life cycle of a type of plant or various types of plants. A light recipe may also comprise control data specific for abnormal events, such as diseases or pests, specific periods, such as germination or harvesting, or accelerated ripening. In particular, a light recipe may comprise information to control light parameters to vary over time. Light recipes may be provided to account for plant parameters such as growth phases or ripening phases of the plants or goods to be harvested. Such plant parameters may be determined by means of sensors, the measured data of which being processed in the control unit, particularly for monitoring the health and growth of the plants (see also the element “Plant Health and Growth” of the disclosure).
According to an exemplary light recipe, those light-emitting elements or light guides situated directly above a plant or a tip of a plant, may be operated at reduced intensity, while those light emitting elements or light guides or parts thereof situated below the tip of the plants may be operated at increased intensity or spectrum, to compensate for the shading effect of higher leaves, or vice versa.
8 th aspect of “Light Guides”: The light module according to any one of the 2 nd to 7 th aspects of “Light Guides”, wherein the light-emitting element provided in a layer closer to the target area is adapted or adaptable to emit light with higher portions of at least one of blue and/or red and/or far-red, and/or infrared and/or ultraviolet compared to the light-emitting element provided in a layer further away from the target area.
As an example, at least one light-emitting element or light guide that is provided in a layer closer to the target area compared to a light emitting element or light guide provided in a layer further away from the target area is adapted to emit light with a higher portion of blue light. Arranging that light emitting element or the respective light guide of this light-emitting element below the uppermost leaves of the plants allows delivery of light with an increased amount of blue wavelengths to the lower parts of the plants. As, commonly, plants in the lower sections do receive a reduced amount of blue light due to the shading and absorption by higher leaves, increased illumination of these lower sections may increase the agricultural output by compensating the shading due to higher leaves. In a similar way, other light spectra can be applied, like red, far-red, infrared, and ultraviolet.
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In particular, the light emitted by such a lower placed light emitting element or light guide can be adjusted, for example with respect to light intensity, or may be spectrally changed over time as a function of plant growth or plant morphology. The light emitting element may thus form a light element, which is spectrally adaptable in a vertical direction. The light emitting element may further be temporally controllable, i.e. spectral composition, light intensity and/or further parameters according to an applicable light recipe may be controlled to vary over time.
9 th aspect of “Light Guides”: The light module according to any one of the 1 st to 8 th aspect of “Light Guides”, wherein the light-emitting element comprises a wire netting, which is arrangeable in a predetermined shape on or over the target area.
In particular, the wire netting may be arrangeable over the plants to be illuminated. More advantageously, the holding means of the lighting fixture may comprise the wire netting. The light guides may be mounted to or attached to the wire netting. That way, light may be delivered more accurately, under definable incident angles and in a more individualized manner. Further, the shape and size of the meshwork may be altered, e.g. over time. Size and shape of the meshwork may be adaptable e.g. to the size and/or morphological state and/or morphological change of the growing plants.
10 th aspect of “Light Guides”: The light module according to any one of the 1 st to 8 th aspect of “Light Guides”, wherein the light guide is braided or twisted around the light-emitting element.
The light guide may in particular be braided or wrapped around the light-emitting element, e.g. a wire netting of the lighting fixture. The wire netting may also be provided as a separate component. In such embodiments, the light-emitting element may be supported by the wire netting or meshwork of the netting.
Fabric
11 th aspect of “Light Guides”: The light module according to any one of the 1 st to 8 th aspect of “Light Guides”, wherein the holding means include or comprise a fabric, with at least one light guide of the at least one light-emitting element being provided on or in the fabric.
The fabric may in particular form a mat-like structure. On or in the fabric, a light guide of the at least one light module is provided.
12 th aspect of “Light Guides”: The light module according to the 11 th aspect of “Light Guides”, wherein the fabric is movably connected with respect to the holding means.
Further, the fabric may be connected movably with respect to the holding means of the light module. In particular, the light guide may be woven into the fabric. The fabric thus may be arranged over the target area, i.e. over the plants to be illuminated. Following the growth of the plants, the fabric may be moved, e.g. raised, in order to keep the distance of the light guides from the plants constant, or, as the case may be, according to an individual or predetermined adjustment or control plan.
The fabric may also be designed rollable. This may facilitate access to the plants for watering, harvesting, visual inspection or other tasks, by simply removing the fabric. Furling or unfurling of the fabric may either be actuated manually or automatically. Furling and unfurling of the fabric may in particular be controlled by a control unit, in some embodiments/implementations by the same control unit, which also controls the light parameters. Providing such a fabric may also allow to store away the fabric, if it is not needed, in a convoluted state. This may reduce storage place and facilitate handling with the light emitting element.
Light Source and Control
18 th aspect of “Light Guides”: The light module according to any one of the 1 st to 17 th aspect of “Light Guides”, wherein the light source of the light emitting element is arranged in a remote position from the light-emitting element.
The light source, in fact, may be placed remote to the vegetated (cultivated) areas, even in separated rooms or on different floors of a vertical farm. That way, heat generated by the light sources or by the control unit or units may be utilized for heating or climate control of the vertical farm, without locally and uncontrollably affecting climate conditions in the vertical farm. The light guides are then provided in order to deliver the light from the light sources to the respective target areas.
A heat pump may be provided, in order to utilize the heat generated by the light sources. Alternatively, a water cycle, ventilation system or similar may be provided in order to utilize the heat generated and to cool the light sources and other components, if required. Heat generated may thus be used for heating in air conditioning systems, warm water supply or such, even in locations remote from the heat source. Alternatively, if need may be, the heat may be redirected to the plants (see also the aspect “Heat Reflector”, below).
Light guides or groups of light guides intended for the same one or more wavelengths or spectral composition may be coupled to light sources, in particular semiconductor light sources, which may be separately controllable. That way, groups of light sources may be formed. “Separately controllable” in this context shall mean that one or more first light sources may be controlled independent from at least one or more second light sources. Control parameter may be, among others, spectral composition, light intensity, emission time and others. A semiconductor light source may emit light of essentially one wavelength or of multiple wavelengths, depending on the type of light source used.
Thus, different layers of a light emitting element or different sections thereof may be provided with an individual light recipe. This may be realized by using light guides of one group or another. That way, light illumination of the plants may be improved, in particular of plant sections below the uppermost leave layer.
Sensors
Accordingly, the at least one light guide can bring light between the leaves of a plant, which may be referred to as inter-canopy lighting. According to various embodiments of the aspect “Light Guides”, sensors, such as optical, thermal, spectral, or other sensors, can be attached to the at least one light guide or implemented within a light guide, to the at least one light emitting element and/or to the light module. The sensors may also be provided independent of a light guide at the light emitting element, the light module, or at any position within the agricultural lighting fixture or connected therewith. “Connected” in this context shall mean any connection, physical or via data connection or any other interaction between sensor and lighting fixture, including common databases or similar.
›SUMMARY OF THE DISCLOSURE · 63 of 73
The sensors may check parameters like temperature, humidity or illumination. The sensors may also be attached to a holding or supporting structure, such as wires, used to hold the crop or any other installation between the crops. The sensors may be used to measure the micro-climate within the canopy, for example air temperature, ventilation, humidity, CO2 concentration, pheromone concentration, concentration of toxic substances released from a plant, and the like. A computing unit considers these data to optimize the growth parameters, e.g. temperature, humidity, light, for the specific plant. The computing unit may be a part of the control unit or provided as a separate element. The sensors could be connected to a power line and to a network line for data transfer. The sensors may also be battery operated. The sensors may transmit data through a data connection, such as LAN, WLAN, Bluetooth, radio, RFID, near field communication or similar.
Agricultural Lighting Fixture
19 th aspect of “Light Guides”: Furthermore, an agricultural lighting fixture, in particular for plant illumination, comprises a control unit and at least one light module according to any one of the 1 st to 18 th aspects, wherein the control unit is adapted to control at least one of light intensity, illumination time, illuminated area, spectral composition of the light, position of at least one light guide, light emitting element or of the light module, in particular as a function of plant growth and/or plant morphology.
Agricultural Lighting fixtures provide lighting of plants, algae, fungi, transgenic plants, and any other edible or useable produce as well as for animals, including transgenic animals, insects, bacteria, and viruses with natural and/or artificial electromagnetic radiation.
Agricultural Lighting is applied in order to influence, stimulate and control the growth and well-being in all stages of the individual development including shoot development, reproduction, morphology, maturation, harvesting and storage. In the following, for the sake of convenience, the term ‘light’ shall encompass the entire electromagnetic wavelength range from the ultraviolet (100 to 400 nm) to the visible (400-780 nm) to the infrared (780 nm to 1 mm) spectral range.
Agricultural lighting fixtures can be part of a fixed, moveable or portable growth or storage place. Agricultural Lighting fixtures can contain light sources, light source drivers and controllers, sensors, optical components, actuators, as well as data storage, processing and one-directional, bi-directional and multi-directional communication devices. Agricultural Lighting fixtures can contain heating and cooling devices as well as heat deflecting devices, such as heat reflective walls (see also the element “Heat Reflector” of the disclosure, below).
Agricultural Lighting fixtures can contain or be made of transparent polymeric materials, translucent materials, and specular or diffusive materials.
Agricultural Lighting fixtures for plant growth can be suited to modulate light generated by the light sources with a rhythmic or aperiodic signal produced artificially or a rhythmic signal extracted from sound present in nature, and can be suited to illuminate a plant with the modulated light.
Agricultural Lighting fixtures can be operated based on the execution of light recipes. Agricultural Lighting fixtures can have individual identifiers, like an RFID chip or a digital signature or IP-address, allowing them to be connected to a computer system or cloud computer network, so that they can be part of an Internet-of-Things (IOT)-system, or connected to an Artificial Intelligence (AI) machine in order to provide useful growth predictions (see also the aspect “Yield Prediction”) and applicable illumination settings.
Agricultural Lighting fixtures can be suited for underwater lighting, sweet and salt water.
Agricultural Lighting fixtures can be part of an Industry 4.0 standard.
Lighting fixtures of agricultural purposes can contain artificial light sources like Light Emitting Diodes (LED) with or without conversion by using a fluorescent substance, commonly referred to as phosphor conversion, Laser diodes, OLED light emitting material on the basis of organic materials, Quantum Dot light emitters, Fluorescent lamps, Sodium low and high pressure lamps, Xenon and Mercury Short Arc lamps, Halogen lamps, and the like. Therefore, such light sources may also be used in a light module according to various aspects of the present disclosure.
Lighting fixtures of agricultural purposes can contain fluorescent or phosphorescent substances, for example applied to the fixture surfaces. The light source of the lighting fixtures of agricultural purposes can be adjusted or be optimized for use in connection to optical components, such as reflectors, symmetrical or asymmetrical lenses, filters and so on.
Lighting fixtures of agricultural purposes can be grouped together or can be arranged in a network or wire-frame manner.
An agricultural lighting fixture can be rotated, for example from lighting top-down to lighting bottom-up at various stages of a rotary growth cabinet.
An agricultural lighting fixture can be made of a flexible material that is formable, e.g. bendable, and can therefore be changed in form and shape. An agricultural lighting fixture may comprise of one or several lighting modules that can be changed, individually or as a group, in their form and/or position thus altering the shape and appearance of the fixture.
Method for Agricultural Management
20 th aspect of “Light Guides”: Furthermore, a method for agricultural management, in particular for plant growth, with a light module according to any one of the 1 st to 18 th aspects, comprises the steps of providing a light-emitting element on or above a target area, in some embodiments/implementations the target area being populated by one or more plants, seedlings and/or seeds, controlling, by means of a control unit, parameters of light being emitted toward the target area, wherein the light emitting element is provided, in some embodiments/implementations movably, in a predetermined distance away from the target area.
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By means of a control unit, parameters of light, which is emitted toward the target area, are controlled. In particular, the control unit may comprise at least one light recipe. The light recipe allows controlling a specific, predetermined or adaptively defined, period of plant growth, including the entire life-cycle of a plant.
The light-emitting element and/or the light guide is provided in a predetermined distance away from the target area. The light-emitting element and/or the light guide may be provided movably, i.e. such that the distance thereof with respect to the target area with the plants, and thus the distance to the plants to be grown, may be varied. That way, the distance between the light-emitting element and the plants may be adjusted, in some embodiments/implementations to an optimal distance in order to provide a desired light recipe. The control unit may be provided to control the distance of the light emitting element to the plants.
According to “Light Guide”, light of different spectral composition, among other parameters, may be provided in different vertical layers, such as above the plants and between the plants, referred to as inter-canopy lighting. Lighting parameters may be set or controlled to vary over time. Variation of lighting parameters may depend on predetermined light recipes and/or data collected, e.g. by means of sensors, and/or manual input. In particular, lighting parameters such as illumination time or spectral composition, and in particular spectral composition or other parameters in different vertical layers, may be defined based on plant growth phases, ripening phases, morphological condition, plant size, but also based on economic factors such as planned harvesting, delivery dates, research and others.
“Failure Detection”
According to the element “Failure Detection” of the disclosure, a controlled agricultural system with a light fixture is proposed that is configured to be able to detect and, in some embodiments/implementations, locate a failing light source quickly so that a repair or replacement action, or any other countermeasure, can be taken promptly.
1 st aspect of “Failure Detection”: More specifically, the controlled agricultural system, comprises a light fixture with a light source for providing agricultural lighting, wherein the Controlled Agricultural System is configured for an automatic failure detection, namely for detecting a reduced emission and/or total failure of the light source.
2 nd aspect of “Failure Detection”: The controlled agricultural system according to the 1 st aspect of “Failure Detection”, comprising a current sensor, the Controlled Agricultural System being configured to measure, for the failure detection, an electrical current of the light fixture and/or the light source.
In a preferred embodiment, a current sensor is provided for measuring an electrical current for the failure detection.
3 rd aspect of “Failure Detection”: The controlled agricultural system according to the 2 nd aspect of “Failure Detection”, wherein the light fixture comprises a plurality of light sources, the Controlled Agricultural System being configured to measure the electrical current of a subset of the light sources and/or individual light sources.
Therein, the current can be measured for the light fixture as a whole or for individual light sources thereof. It is also possible to measure the current not for each light source individually but in groups, still allowing at least a certain localization of the failing light source. Combinations are possible as well, for instance a measurement in groups (coarse localization) with a subsequent measurement of the light sources within the respective group (fine localization). For measuring the current through the light sources individually and/or in groups, in some embodiments/implementations a plurality of electrical current sensors are provided.
The agricultural system, in particular a computing device thereof, can be configured for comparing the current or current/power consumption evaluated by the current sensor with a target value. The target value can be fixed or in some embodiments/implementations depend from the lighting conditions applied, for instance be lower in case of a lower intensity and vice versa. A deviation from the target value can indicate a problem with the light fixture/light source. For instance, in case of a LED light source, a bond wire lift off or other damage of the electrical wiring can be detected as an open load.
In general, the light fixture typically comprises a plurality of light sources, in some embodiments/implementations light sources having different spectral properties. In some embodiments/implementations the light sources are LEDs.
4 th aspect of “Failure Detection”: The controlled agricultural system according to any one of the 2 nd or 3 rd aspect of “Failure Detection”, wherein the light sources belong to a light fixture assembled from exchangeable modules, each module comprising a plurality of light sources respectively, the Controlled Agricultural System being configured to measure the electrical current for each module individually.
In a preferred embodiment, the light fixture comprises at least two exchangeable modules, each of them comprising a plurality of light sources. When a light source fails, the respective module can be replaced as a whole by a new module, allowing for a quick installation and short down time. In a respective multi-module light fixture, the current measurement can in some embodiments/implementations be performed for each module individually.
5 th aspect of “Failure Detection”: The controlled agricultural system according to any one of the 2 nd to 4 th aspect of “Failure Detection”, comprising a computing device configured for comparing at least one of the current measured and a current consumption derived therefrom with a target value.
6 th aspect of “Failure Detection”: The controlled agricultural system according to the 5 th aspect of “Failure Detection”, wherein the target value considers an ageing effect, namely depends from the service life of the light fixture and/or the light source.
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In a preferred embodiment, the computing device of the agricultural system is configured for comparing the measured current or current consumption with a current value depending on the service life of the light fixture or light source. This means, aging effects are considered, enabling a decision on whether a current drift or drop results from an actual failure or lies within the normal aging. Any target value referred to in this disclosure can be stored in a data storage device of the agricultural system or externally, for instance in the cloud.
7 th aspect of “Failure Detection”: The controlled agricultural system according to any one of the 1 st to 6 th aspect of “Failure Detection”, comprising a light sensor, the Controlled Agricultural System being configured to measure, for the failure detection, a light intensity value of the light source and/or the light fixture.
Alternatively or in addition to the electrical current measurement, a light sensor can be provided for the failure detection. A drop of the light intensity measured by the sensor can indicate the failing light source or light fixture.
8 th aspect of “Failure Detection”: The controlled agricultural system according to the 7 th aspect of “Failure Detection”, wherein the light sensor is arranged in a growth area having growth locations for growing plants.
The light sensor or an array with a plurality of light sensors can be arranged in the growth area, namely in the area where the plants are grown. Assuming a top down illumination, the light sensor can be oriented upwards to the light fixture. Typically, a plurality of light fixtures are provided above a growth area. In general, an external light sensor can be advantageous as it can be oriented towards a light exit surface of the light fixture, detecting directly the light emitted there.
9 th aspect of “Failure Detection”: The controlled agricultural system according to the 8 th aspect of “Failure Detection”, wherein the light sensor is integrated into the light fixture.
Alternatively, it is also possible to integrate the light sensor into the light fixture. The light sensor can for instance be oriented towards the growth area, detecting light reflected or scattered there.
10 th aspect of “Failure Detection”: The controlled agricultural system according to the 9 th aspect of “Failure Detection”, wherein the light fixture comprises a lens for guiding light emitted by the light source to a growth location, wherein the light sensor is optically coupled to the lens.
When the light fixture comprises a lens for guiding the light towards the growth area, the light sensor can in some embodiments/implementations be arranged at an edge thereof. The lens can be a converging or convex lens for instance, focusing the light on the growth area. Most of the light emitted by the light sources of the light fixture will travel through the lens to the growth field. However, some reflection can occur at the interfaces, for instance a total internal reflection or Fresnel reflection.
11 th aspect of “Failure Detection”: The controlled agricultural system according to the 10 th aspect of “Failure Detection”, wherein the light sensor is arranged at an edge of the lens to receive a part of the light, which is guided in the lens by total internal reflection.
By placing the light sensor at the edge of the lens, the light reflected sideward can be used for the intensity measurement.
12 th aspect of “Failure Detection”: The controlled agricultural system according to the any one of the 7 th to 11 th aspects of “Failure Detection”, comprising a plurality of light sources, a plurality of light sensors, and a computing device, wherein the computing device is configured for locating the light source with the reduced emission and/or total failure by comparing light intensity values measured by the light sensors.
In a preferred embodiment, the controlled agricultural system comprises a plurality of light sensors. Each of them can be connected to a control unit. This can be a common one for several sensors or individual units for each sensor.
The measured intensity values can be collected in a computing device. In some embodiments/implementations the latter is configured for locating the failing light source or light fixture by comparing the intensity values measured by the different light sensors.
This localization can be achieved by a triangulation procedure. The position of the individual light sensors and light sources is known by the computing device, so that the area calculated by triangulation based on the sensor signals can easily be matched with the position of the light source. Depending on the distances between the light sensors and the failing light source or fixture, the measured intensity will drop more or less. With target values of the intensities stored (calculated or measured upfront), a drop profile results, enabling the failure spot location.
13 th aspect of “Failure Detection”: The controlled agricultural system according to the any one of the 7 th to 12 th aspects of “Failure Detection”, comprising a computing device and a sunlight sensor for measuring a sunlight intensity value, wherein the computing device is configured to evaluate the light intensity value measured by the light sensor for the failure detection whilst considering the sunlight intensity value.
In a preferred embodiment, the controlled agricultural system comprises an additional sunlight sensor. Likewise, in case of a greenhouse or glasshouse, or in case of an outdoor farm, the sunlight intensity can be considered when the light intensities measured for the failure detection are evaluated, as the intensity of the sunlight can vary depending on the weather (cloudy or bright sky) and daytime. With the sunlight sensor, this “background intensity” can be measured, enabling a differentiation of natural and artificial variations of the lighting.
14 th aspect of “Failure Detection”: The controlled agricultural system according to the any one of the 7 th to 13 th aspects of “Failure Detection”, comprising a plurality of light sources, the Controlled Agricultural System being configured for modulating the emission of at least one light source temporarily, namely to impose a defined pattern, wherein a computing device of the Controlled Agricultural System is configured to allocate the light intensity measured by the light sensor to the at least one light source.
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In a preferred embodiment, the controlled agricultural system is configured for modulating the emission of at least one light source temporarily. This can for instance be controlled by the computing device connected to a control unit of the light fixture, or light source. In general, the modulation could even be predefined in the control unit of the light fixtures. With the modulation, a pattern is imposed on the emission, for instance a periodical intensity change or a switch on/off routine.
The light intensity measured shows the same modulation. By an evaluation of this signal, for instance by a Fourier Transformation, the pattern can be read out. The modulation/pattern is a direct link between the light source and the measured intensity. Accordingly, an intensity change, for instance an intensity drop, can be assigned to the respective light source/light fixture.
15 th aspect of “Failure Detection”: The controlled agricultural system according to the any one of the 7 th to 14 th aspects of “Failure Detection”, comprising a plurality of light sources, the Controlled Agricultural System being configured to trigger a clocked emission of the light sources in a measuring interval.
In a preferred embodiment, the controlled agricultural system is configured for triggering, in a measuring interval, a clocked emission of the light sources, either individually or in groups. The light sources emit one after the other so that the light intensity measured at different points in time can be assigned to the different light sources. The duration of the measuring interval can be in the range of seconds or milliseconds. The same time scale can be of interest for the modulation mentioned above.
16 th aspect of “Failure Detection”: The controlled agricultural system according to the any one of the 7 th to 15 th aspects of “Failure Detection”, comprising a plurality of light sources having different spectral properties and a plurality of light sensors having different spectral sensitivities, a computing device of the Controlled Agricultural System being configured to correlate light intensity values measured in different spectral ranges with the light sources ( 300 , 400 ) having different spectral properties.
In some embodiments/implementations, a plurality of light sensors with different spectral sensitivities can be provided. The spectral sensors can either measure the total spectral range or their spectral sensitivity can fit to the maxima of the emission of the light sources used. Thus, it is possible to determine which spectral region is affected, namely which light source type is failing.
The element “Failure Detection” of the disclosure also relates to a method for controlling a controlled agricultural system, wherein a reduced emission of total failure of a light source is detected.
17 th aspect of “Failure Detection”: More specifically, the method for agricultural management, according to any one of the 1 st to 16 th aspects of “Failure Detection”, comprises at least one controlled agricultural system, wherein a reduced emission and/or total failure of a light source is detected. Regarding further details, reference is made to the description above.
The element “Failure Detection” is also applicable to a group of light fixtures (luminaires) irradiating the same agricultural space. In one embodiment, all but one light fixture can be switched off for a predefined time window (measurement time interval) so that the sensors measure the irradiation from the operating light source (as described above), which is then repeated analogously for the other fixtures. Alternatively, all fixtures can stay in operation mode, wherein during each measuring time interval each fixture (the light sources thereof) is individually modulated (for example using a set of different PWM techniques) thus enabling a simultaneous measurement of all fixtures with the same sensors.
Further, the element “Failure Detection” also relates to a computer program comprising program instructions, which, when executed by a computing device, execute the aforementioned method.
18 th aspect of “Failure Detection”: Computer program product, comprising a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 16 th aspects of “Failure Detection”, cause the Controlled Agricultural System to execute the Method for Controlling a Controlled Agricultural System according to the 17 th aspect of “Failure Detection”.
“Failure Compensation”
According to the element “Failure Compensation” of the disclosure, a controlled agricultural system with a light fixture is proposed that is configured to be able to compensate a failing light source, namely a reduced emission or even total failure, at least temporarily, until the failed light source, affected module, or the light fixture as a whole, is replaced or repaired.
1 st aspect of “Failure Compensation”: More specifically, the controlled agricultural system comprises a plurality of light sources for providing agricultural lighting, wherein the controlled agricultural system is configured for compensating a reduced emission and/or total failure of a failing light source by an emission of another light source.
For instance, upon detection of the failing light source, an alert message can be issued, informing operating personnel about the failure. However, a replacement of the failing light source is often not possible instantaneously, depending for instance on the availability of an electrician or the accessibility of the respective region of the farm. In terms of preventing a contamination or the like of the plants, accessibility can be restricted, depending for instance on the growth cycle.
In this respect, compensating a failing light source according to the disclosure can prevent the plants from being illuminated insufficiently at least temporarily, namely until the light source is repaired or replaced. Even a temporary insufficient illumination, for instance in terms of the intensity or the spectral composition, can negatively impact the growth of the plants.
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The light sources may be configured to emit radiation in the visible and/or the non-visible spectral range, as for example in the far-red range and/or in the UV-B region of the electromagnetic spectrum. It may be configured to emit monochromatic light, e.g. green 525 nm, or narrow band radiation with a Full Width At Half Maximum (FWHM) smaller than 50 nm, or broadband radiation with a Full Width At Half Maximum (FWHM) greater than 100 nm. The light sources may be an integral part of the light fixture as well as a remote yet connected element. It may be placed in various geometrical patterns, distance pitches and may be configured for alternating of color or wavelength emission or intensity or beam angle. The fixture and/or light sources may be mounted such that they are moveable or can be inclined, rotated, tilted etc. The fixture and/or light sources may be configured to be installed inside a building or exterior to a building. In particular, it is possible that the light sources or selected light sources are mounted such or adapted to being automatically controllable, in some embodiments/implementations remotely, in their orientation, movement, light emission, light spectrum, sensor etc.
The light sources may be selected from the following group or a combination thereof: light emitting diode (LED) including a phosphor conversion LED or pc-LED using a fluorescent and/or phosphorescence substance for conversion, laser diode (LD), laser activated remote phosphor (LARP), Organic Light sources such as OLED, quantum dot based light sources, solar radiation, an incandescent lamp, a halogen lamp, a Xenon or Mercury short arc lamp, a fluorescent lamp, a high pressure discharge lamp and a low pressure discharge lamp.
Below, two options for realizing the compensation of the failing light source are discussed.
2 nd aspect of “Failure Compensation”: The Controlled Agricultural System according to the 1 st aspect of “Failure Compensation”, wherein the other light source is also switched on in normal operation prior to the compensation, its emission being increased for the compensation.
The light sources can typically be arranged array- or matrix-like. When one of the light sources is detected as failing, this can be compensated by an increased output of one or more surrounding light sources. Using more than one light source for the compensation can be preferred in general, in terms of homogeneity and in terms of avoiding an overload of the light sources used for the compensation.
3 rd aspect of “Failure Compensation”: The Controlled Agricultural System according to the 2 nd aspect of “Failure Compensation”, wherein the light sources belong to a light fixture comprising a plurality of light sources, the Controlled Agricultural System being configured for choosing the other light source for the compensation on the basis of at least one of the criteria spatial proximity and spectral matching.
In a preferred embodiment, the light source(s) driven with a higher emission for the compensation is/are chosen depending on the spatial proximity and/or the spectral matching. Thus, those light sources, which are close to the failing light source and have a comparable or identical spectral composition or emission wavelength are chosen to compensate the failing light source. As discussed below, in some embodiments/implementations the respective decisions are taken automatically, for instance by a computing device. In particular, neuronal learning or other artificial intelligence techniques can be applied to optimize the decision taking.
4 th aspect of “Failure Compensation”: The Controlled Agricultural System according to the 2 nd or 3 rd aspect of “Failure Compensation”, wherein the light sources belong to a light fixture assembled from exchangeable modules, each module comprising a plurality of light sources respectively, wherein the Controlled Agricultural System is configured for choosing the other light source within the module of the failing light source.
In a preferred embodiment, the agricultural system is equipped with one or more light fixtures, wherein the light fixtures are assembled from exchangeable modules respectively. Each module comprises a plurality of light sources. Therein, the light sources within a module can have the same spectral properties or can have a different emission wavelength.
5 th aspect of “Failure Compensation”: The Controlled Agricultural System according to the 4 th aspect of “Failure Compensation”, configured for compensating the failing light source only within the module of the failing light source.
In some embodiments/implementations, the controlled agricultural system is configured for choosing the light source for compensating the failing light source within the same module. Basically, light sources of other modules can be used in addition. However, particularly preferred, solely the module of the failing light source is used for the compensation, i.e. no other light sources belonging to another module. This can be advantageous, as the high current operation required for the compensation can reduce the life time of the light sources which is less critical when the module is exchanged anyway (since the failing light source has to be exchanged by exchanging said module).
6 th aspect of “Failure Compensation”: The Controlled Agricultural System according to the 1 st aspect of “Failure Compensation”, wherein the other light source is redundant, namely is switched off prior to the compensation and switched on for the compensation.
An alternative approach to compensate the failing light source is to provide one or more redundant light sources. As long as no failing light source is detected, the redundant light source(s) is/are switched off. Providing a redundant light source could also be combined with using normal operation light sources for the compensation. In some embodiments/implementations, these are alternatives, one of them being chosen for the agricultural system.
7 th aspect of “Failure Compensation”: The Controlled Agricultural System according to the 6 th aspect of “Failure Compensation”, wherein the light sources belong to a light fixture comprising a plurality of redundant light sources switched off during normal operation.
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In a preferred embodiment, a plurality of redundant light sources are provided in a respective light fixture. Particularly preferred, each interchangeable module of the light fixture can be provided with one or more redundant light sources. Regarding their spatial alignment, a rather equal distribution of the redundant light sources can be preferred, even so not required in general. The redundant light sources can have different wavelengths, the composition/mixture being adapted to the normal operation light sources.
8 th aspect of “Failure Compensation”: The Controlled Agricultural System according to any one of the 1 st to 7 th aspect of “Failure Compensation”, wherein the light sources belong to a light fixture comprising a plurality of light sources and a sensor device for sensing the reduced emission and/or total failure of the failing light source.
In a preferred embodiment, a light fixture comprising the light sources (normal operation and/or redundant) comprises also a sensor device for sensing the failing light source. For instance, a current sensor can be provided for detecting a change of the current through the respective light source. Alternatively or in addition, an optical or light sensor, for instance a photodiode, can be provided for measuring the light.
9 th aspect of “Failure Compensation”: The Controlled Agricultural System according to any one of the 1 st to 8 th aspect of “Failure Compensation”, comprising an actuator device for adjusting the emission of the light source and a computing device coupled with the actuator device and configured to cause the actuator device to compensate the failing light source by the emission of the other light source.
In a preferred embodiment, the controlled agricultural system comprises an actuator device for adjusting the emission of the light source, for instance a drive unit adjusting the current through the light source. The actuator device can be integrated into the light fixture or provided externally. Further, the agricultural system comprises a computing device which is coupled to the actuator device. The coupling of individual components, for instance the actuator device and the computing device, can be achieved wire-based or wireless, any known interface can be used (WLAN, LAN or Bluetooth for instance). The computing device is configured to cause the actuator device to compensate the failing light source as described above. Since the failing light source is known, the computing device can decide which light source (spectral properties/position) has to be driven with the appropriate intensity to achieve the compensation.
10 th aspect of “Failure Compensation”: The Controlled Agricultural System according to the 9 th aspect of “Failure Compensation”, comprising a data storage device or being linked to a data storage device linked to the computing device, a data set being stored in the data storage device, wherein the data set comprises data on ageing properties of the light sources, the computing device being configured for assessing the failing light source based on the ageing properties.
In some embodiments/implementations, the controlled agricultural system comprises a data storage device linked to the computing device. Therein, a data set is stored in the data storage device, which comprises data on the ageing properties of the light source(s). With such data, the decision about which light source has to be considered as the failing one could even be taken without any measurement at all. The system knows upfront the time of life and when a compensation becomes necessary because the emission decreases. However, in some embodiments/implementations, the ageing data is used in combination with the sensor detection, increasing the overall reliability of the decision taking.
11 th aspect of “Failure Compensation”: A Method for Controlling an Agricultural System, comprising a plurality of light sources, wherein a reduced emission and/or total failure of a failing light source is compensated by an emission of another light source.
Furthermore, reference is made to the description above, the features described there shall also be disclosed in terms of the method.
12 th aspect of “Failure Compensation”: The Method for Controlling an Agricultural System according to the 11 th aspect of “Failure Compensation”, for controlling a Controlled Agricultural System according to any one of the 1 st to 10 th aspect of “Failure Compensation”.
13 th aspect of “Failure Compensation”: Computer program product, comprising a plurality of program instructions, which when executed by a computing device of a Controlled Agricultural System according to any one of the 1 st to 10 th aspect of “Failure Compensation”, cause the Controlled Agricultural System to execute the Method for Controlling an Agricultural System according to the 11 th or 12 th aspect of “Failure Compensation”.
“Heat Reflector”
According to the element “Heat Reflector” of the disclosure, a horticultural apparatus is proposed, particularly for use in a controlled agricultural system, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, particularly a plant growing facility and/or an aquaponics facility, which comprises an agricultural light fixture and a heat reflector that is able to direct or redirect the heat generated by the agricultural light fixture to the plants.
1 st aspect of “Heat Reflector”: More specifically, the horticultural apparatus, particularly for use in a Controlled Agricultural System, comprises an agricultural light fixture, comprising at least one light module, configured for illuminating plants arranged on a cultivated area below the agricultural light fixture, a heat reflector arranged above the agricultural light fixture and configured to be able to reflect heat, emanating upwards from the agricultural light fixture, downwards to the plants.
Cooling of the LEDs is mainly done by heat conduction (through heat spreaders) and heat convection (through the air). During operation, due to cooling effects, the air above an agricultural light fixture comprising LED is hotter than the air below the agricultural light fixture. To heat the plants, however, more heat underneath the agricultural light fixture is needed. This can be achieved by installing a (heat) reflector above and/or attached to the agricultural light fixture. The reflector traps the heat (hot air) below. Furthermore, the reflector may comprise an infrared-reflecting surface, e.g. based on gold-, silver- or a dielectric coating, which reflects radiation, in some embodiments/implementations in the infrared range. Other coating ad/or heat reflective materials are for example, birefringent dielectric multilayer films and two-component infrared reflecting films comprising alternating layers of first and second diverse polymeric materials, Consequently, such a reflector reflects infrared radiation down to the plants, thus heating the plants and improving their growth, while recovering the heat energy which would have been lost otherwise.
›SUMMARY OF THE DISCLOSURE · 69 of 73
2 nd aspect of “Heat Reflector”: The horticultural apparatus according to the 1 st aspect of “Heat Reflector”, comprising at least one ventilator configured to be able to direct the heat from the agricultural light fixture towards the heat reflector by means of forced convection.
The air convection from the agricultural light fixture to the reflector and thus the transportation of heat can be improved by arranging ventilators on the top face of the agricultural light fixture, which cool the LEDs by creating an airflow that directs the air towards the reflectors.
3 rd aspect of “Heat Reflector”: The horticultural apparatus according to the 1 st or 2 nd aspect of “Heat Reflector”, wherein the heat reflector comprises a plane arranged parallel to the top side of the agricultural light fixture.
In first basic embodiment, the reflector comprises a plane made e.g. of metal, plastics or glass, which is attached or mounted above the agricultural light fixture, in some embodiments/implementations aligned parallel to the agricultural light fixture. In some embodiments/implementations, the surface area covered by the reflector is at least as large as the surface area covered by the agricultural light fixture.
4 th aspect of “Heat Reflector”: The horticultural apparatus according to the 1 st or 2 nd aspect of “Heat Reflector”, wherein the heat reflector is shaped such that the heat emanating from the top side of the agricultural light fixture is first reflected sideways and then downwards, i.e. around the agricultural light fixture towards the plants.
In another embodiment, the reflector is shaped to be able to reflect the heat around the agricultural light fixture. For instance, an appropriate form of the reflector first reflects the heat sideways and then downwards (see for instance FIG. 2).
5 th aspect of “Heat Reflector”: The horticultural apparatus according to any one of the 1 st to 4 th aspects of “Heat Reflector”, wherein the heat reflector comprises two or more movable parts that constitute the reflecting surface.
Furthermore, the reflector may also be partitioned in two or more separate parts that can be (automatically or by temperature sensor feedback control loop) moved apart (split) thus creating openings for carrying some of the heat away by means of upwards airflow while reducing the heat radiation downwards, and vice versa.
6 th aspect of “Heat Reflector”: The horticultural apparatus according to the 5 th aspects of “Heat Reflector”, wherein the two or more parts that constitute the reflecting surface are configured to be able to move apart thereby forming between the two parts an aperture where heat can escape, enabling to control the amount of heat reflected towards the plants.
7 th aspect of “Heat Reflector”: The horticultural apparatus according to the 5 th or 6 th aspects of “Heat Reflector”, wherein at least one movable parts is configured to be able to adjust the direction of the reflected heat.
Furthermore, the orientation or inclination of the ventilators and/or the reflectors and/or parts of the reflectors may be adjustable, so that the heat can be directed in certain directions, e.g. to increase the heat in certain areas depending on the applied growth recipe.
8 th aspect of “Heat Reflector”: The horticultural apparatus according to any one of the 1 st to 7 th aspects of “Heat Reflector”, comprising at least one supplemental heat source.
Furthermore, a supplemental heat source may be added to the agricultural light fixture to enhance the heating if necessary.
It should also be noted that a heat reflector can contain heat absorbing and heat storing materials (like phase transition materials) and thus release thermal energy even after the light sources were switched off.
It should also be noted that a heat reflector that is for example correlated with a specific fixture, can be connected to another heat reflector of a second lighting fixture thus allowing transfer of heat across two or multiple heat reflectors.
Furthermore, a solar panel or photovoltaic cells may be attached to the upper side of the reflector. Together with the reflector, the solar panel or the photovoltaic cells can help to shade the agricultural light fixture against heat from the sun in a greenhouse and at the same time generate additional energy to supply e.g. the agricultural light fixture or, as the case may be, sensors or ventilators.
9 th aspect of “Heat Reflector”: A Controlled Agricultural System, comprising at least one horticultural apparatus according to one of the 1 st to 8 th aspect, a computing device, configured to be able to control the horticultural apparatus according to a growth recipe.
More specifically, the controlled agricultural system is configured to be able to adjust the heat reflector, e.g. its position, alignment, shape, according to a growth recipe. The growth recipe comprises a light recipe, and it may also comprise temperature values appropriately correlated to the light recipe.
10 th aspect of “Heat Reflector”: The Controlled Agricultural System according to the 9 th aspect of “Heat Reflector”, wherein the growth recipe comprises a light recipe and correlated temperature values, measured for example at plant level.
It should be noted that temperature sensors can be attached to the reflective planes or be integrated into them, thus allowing measurement of the local reflector temperatures in real time. The horticultural light fixture and/or the heat reflector may be controlled such that the illumination and the temperature at the plants match with the growth recipe.
11 th aspect of “Heat Reflector”: The Controlled Agricultural System according to the 9 th or 10 th aspect of “Heat Reflector”, comprising an actuator device configured to be able to control the position/alignment and/or the shape of the heat reflector.
Furthermore, as the case may be, ventilators and/or supplemental heat sources, arranged at the agricultural light fixture, may also be controlled by the computing device via the actuator device and/or any other suitable control unit.
›SUMMARY OF THE DISCLOSURE · 70 of 73
12 th aspect of “Heat Reflector”: The Controlled Agricultural System according to any one of the 9 th to 11 th aspect of “Heat Reflector”, comprising a data storage device for storing the growth recipe and/or control data for controlling the ventilator and/or control data for controlling the heat reflector.
The data storage device may comprise a database in which growth settings, including light recipes and correlated temperature values, for example measured at plant level, for various plants species are stored.
Furthermore, the computing device is configured to control the actuator device, including the heat reflector, and the agricultural light fixture, including—as the case may be—ventilators and/or supplemental heat sources arranged at the agricultural light fixture, according to the growth recipe stored on the data storage device.
The element “Heat Reflector” of the disclosure also relates to a method for agricultural management, particularly for breeding, growing, cultivating and harvesting in an agricultural facility, particularly a plant growing facility and/or an aquaponics facility, which enables to redirect the waste heat of the light fixture to the plants.
13 th aspect of “Heat Reflector”: A method for agricultural management, comprising the steps of arranging an agricultural light fixture above plants arranged on a cultivated area, illuminating the plants with the agricultural light fixture, arranging a heat reflector above the agricultural light fixture such that heat, emanating upwards from the agricultural light fixture, is reflected downwards to the plants.
14 th aspect of “Heat Reflector”: The method for agricultural management according to the 13 th aspect of “Heat Reflector”, further comprising the step of configuring the heat reflector such that heat, emanating upwards from the agricultural light fixture, is first reflected sideways and then downwards, i.e. around the agricultural light fixture towards the plants.
Accordingly, the heat generated by the light sources of the light fixture, particularly LEDs, can be used to increase the temperature of the plants, thus improving the plant growth and recovering the heat energy.
15 th aspect of “Heat Reflector”: The method for agricultural management according to the 13 th or 14 th aspect of “Heat Reflector”, for controlling a Controlled Agricultural System according to any one of the 9 th to 12 th aspect of “Heat Reflector”.
The measures described above according to “Heat Reflector” allow establishing, maintaining and adjusting a specific microclimate around plants or even a single plant.
16 th aspect of “Heat Reflector”: A computer program product, comprising a plurality of program instructions, which when executed by a computer system of an Controlled Agricultural System according to any one of the 9 th to 12 th aspect of “Heat Reflector”, cause the Controlled Agricultural System to execute the Method for Agricultural Management according to any one of the 13 th to 15 th aspect of “Heat Reflector”.
After detecting a malfunction of a luminaire according to “Failure Detection”, failing light sources can be compensated according to “Failure Compensation”. Such detecting and compensating can be applied to luminaires, for instance, of the kind described in “Reflector heat” or “Light Guides”.
The aspects of “Optical Arrangements” may be combined with various aspects of “Light Guides” for further enhancing the efficiency of irradiation to a plant bed. The measures proposed in “Light Guides” and “Optical Arrangements” can further be enhance with various aspects of “Extended Light Recipes”.
UV-light can be used to destroy insects (see group “Plant Health & Growth” of the disclosure). Other wavelengths in the visible range or near infrared range can be used to provide photons to the plant to trigger specific hormone production, or other plant reactions, which are related to specific wavelengths. “Heat Reflector” describes an add-on to a luminaire, which can influences the plant growth (see group “Light/Growth Recipes” of the disclosure).
Smart Grid
According to the element “Smart Grid” of the disclosure, a controlled agricultural system with a connection to a smart grid is proposed. Furthermore, the agricultural system is configured to withdraw more current during times of a great electricity supply (i.e. low price) and withdraw less current in times of a lower supply (i.e. high price), by dynamically adjusting the light recipes for the plants.
The system uses growth recipes (see e.g. “Customized Requirements”). A growth recipe consists of values for light recipe (spectrum, intensity, photoperiod), CO2, temperature, humidity, nutrients, EC, pH, H2O, etc.
The growth recipe has an optimum value and value ranges for good, sufficient and short-term tolerable. Optimum values are self-explaining. Good values are high efficient values which lead to good economics, sufficient values keep the plants growing but slow and/or in not good quality and/or quantity, short-term tolerable values are values where the plant could live/grow for a short-term (e.g. 5 min.) but thereafter would die or have diseases.
To reduce/increase energy consumption, actuators could be orchestrated according to these values, but also production preparation activities (e.g. seeding) and post-production activities (e.g. cleaning of trays) could be shifted. Actuators could be water pumps, HVAC systems, lighting system, internal transportation/logistics, harvesting robots, production systems like seeding machines.
Different optical and ambient sensors are tracking all relevant data and a computer unit onsite or in the cloud is analyzing the data, e.g. due to the sensor data available from a substrate moisture sensor, it can be calculated how long the irrigation pumps can be shut down. Also with the data from optical/image plant sensors it can be detected if stress in the plant occurs and reduce cooling, irrigation etc., within the tolerance level of the plant.
In case of light treatments/adjustments, light might be switched off (or only the energy intensive part of the spectrum could be switched off or reduced), depending on the plants. For some plants, the light intensity can be reduced to the compensation point. The (light) compensation point is the light intensity on the light curve where the rate of photosynthesis exactly matches the rate of cellular respiration. At this point, the uptake of CO 2 through photosynthetic pathways is equal to the respiratory release of carbon dioxide, and the uptake of O 2 by respiration is equal to the photosynthetic release of oxygen. Keeping the illumination above the compensation point prevents the plant from losing energy.
›SUMMARY OF THE DISCLOSURE · 71 of 73
However, when doing this, the reaction of the plant to high or low illumination has to be taken into account. There are long day and short day plants whose activities depend on the length of the day. Example Cannabis : This is a short day plant; if the critical day length will be shorter than ˜14 hours (depending on variety) they will initiate flower; this would be bad if the branching of the plants were not complete and it would result in a lower biomass/flower production.
1 st aspect of “Smart Grid”: More specifically, a controlled agricultural system with a connection to a smart grid, comprises an acquisition unit for acquiring data from the smart grid, a computing device connected to the acquisition unit and configured to calculate a dynamic light recipe for a plant to be illuminated using the data from the smart grid, a control unit connected to the computing device, a light fixture connected to the control unit and configured to convert the dynamic light recipe into control signals for the light fixture and thereby produce a light intensity curve and/or a spectrum curve of the light fixture.
The smart grid provides information about energy costs, and so energy-intensive apparatuses can be operated at times when the prices are low (or is even offered credit if electricity is taken from the grid) because the demand is low or the supply is high (such as on very windy days, for example).
The agriculture system is calculating and showing the grower the cost estimation and revenue potential per project based on the utility company data, especially in case of grid stress. Based on that the agriculture system develops the best possible cost-revenue production planning and gives recommendations to the grower if it is economically reasonable if extra energy should be taken and for how long.
In addition, the status of the production has to be taken into account (provided e.g. by real-time sensor data) to see if any deviations from the production plan due to higher or lower availability of energy is acceptable.
The grower, of course, can define projects as mandatory so that they are executed as planned in any case. These settings are considered in the remaining production planning.
A step-by-step approach to supply more power to the system over time could make sense for user acceptance. Therefore, at the beginning the system is just giving notifications/recommendations regarding flexing of the smart grid. Later on the system decides and implements the growth conditions totally independent.
In case of grid stress, the amount of electricity to be taken from the grid, prices and duration for how long the electricity should be taken will be provided (the system generally provides the price level and the electricity availability).
To take into consideration the availability of (cheap) energy for production planning, the controlled agricultural system may comprise an API to a weather forecast system and an API to the utility company is beneficial to get real-time data and to perform the smart grid approach. The system can also contain an API to a growth recipe input providers.
With the help of price information items from the past and weather forecasts, it is possible to identify when the electricity price will be low or negative.
Furthermore, it is also possible to use time-zone effects, e.g. the import of electricity from EU or other countries that are already in the “night phase”—or are currently consuming less energy.
Therefore, the controlled agricultural system according to “Smart Grid” serves to balance the electricity consumption in a smart grid (“grid balancing”).
2 st aspect of “Smart Grid”: The controlled agricultural system according to the 1 st aspect, comprising an energy storage configured to be able to receive electrical energy in the case of an electricity surplus and/or in the case of a cheap electricity rate in the smart grid.
3 nd aspect of “Smart Grid”: The controlled agricultural system according to the 1 st or 2 nd aspect, comprising an energy storage configured to be able to output electrical energy in the case of an electricity deficit and/or in the case of an expensive electricity rate in the smart grid.
In a preferred embodiment, the vertical farm can have local energy storages in order to capture brief times of surplus or deficit. Consequently, the vertical farm can serve as a battery in the smart grid. Furthermore, energy can be stored in the local energy storages when prices for electrical energy are low and used for operating the controlled agricultural system when prices for electrical energy are high.
The acquisition unit is configured to be able to acquire, e.g. via the Internet or other databases, store and evaluate the energy costs (in some embodiments/implementations electricity in this case).
Furthermore, according to “Smart Grid”, a method for agriculture/agricultural management is proposed that balances the electricity consumption of the controlled agricultural system according to the supply from a smart grid power supply.
4 th aspect of “Smart Grid”: A method for agriculture, comprising a controlled agricultural system according to any one of the 1 st to 3 rd aspect of “Smart Grid” and the following method steps: acquiring data, in particular the electricity price, from the smart grid by the acquisition unit, calculating a dynamic light recipe for a plant to be illuminated by means of the computing unit, taking account of the data, in particular the electricity price and/or the available amount of electricity, from the smart grid, actuating the light fixture by the control unit, which converts the dynamic light recipe from the computing device into corresponding control signals for the light fixture, as a result of which a light intensity or light intensity curve is produced by the light fixture.
5 th aspect of “Smart Grid”: The method for agriculture according to the 4 th aspect of “Smart Grid”, comprising the step of predicting the curve of the electricity price by means of the computing device based on the data from the smart grid.
›SUMMARY OF THE DISCLOSURE · 72 of 73
6 th aspect of “Smart Grid”: The method for agriculture according to the 5 th aspect of “Smart Grid”, comprising the step of taking account of the predicted curve of the electricity price when calculating the dynamic light recipe by means of the computing device.
The controlled agricultural system moreover comprises a computing device, which is configured to be able to predict the curve of the electricity price with the aid of the smart grid when using the acquisition unit, for example using historical data of the electricity curve depending on parameters such as time or weather.
The computing device is configured to render the light recipes dynamic. By way of example, the DLI is known on account of the available, static light recipes. The dark times of the plants and, possibly, other parameters are likewise known. The computing device now knows the target spectrum over time, i.e., the energy consumption over time. It has available a prediction of the energy availability and, using this, it is able to calculate what energy, i.e., light intensity, can be made available at what time. The computing device now optimizes (minimizes) the costs for the energy supply, with it being ensured that boundary parameters such as the entire photon flux per day required by the plants is reached but also that dark times (i.e. rest periods of the plants) are observed.
These information items are then transmitted to the control units (light control units) of the light fixtures (agricultural light fixtures), said control units actuating the light fixtures according to this profile. Depending on the electricity price, the profile substantially changes in terms of the overall intensity and/or the actuation of the individual light colors or spectral regions. Initially, the relative intensity of the individual wavelength regions with respect to one another remains unchanged. However, it is also conceivable for the spectrum itself to change as a consequence of rendering the spectrum dynamic.
By way of example, it is conceivable that the spectrum is restricted in a targeted manner to those LEDs that produce electricity efficiently such that the daylight sum can be obtained with low costs (e.g., the light fixture can actuate only blue LEDs and deactivate other colors that operate less efficiently since the light is converted therein, or only operate said other colors in dimmed fashion).
Moreover, it is possible to undertake a change between different light sources and/or change a mode of operation of different light sources by means of the control unit that is connectable to a smart grid. By way of example, in the case of a mixed illumination, there can be a change from a predominant illumination with conventional halogen or discharge lamps to a predominant illumination using light-emitting diodes, and vice versa.
7 th aspect of “Smart Grid”: The method for agriculture according to any one of the 4 th to 6 th aspect of “Smart Grid”, comprising the step of absorbing a brief electricity surplus by way of correspondingly increasing the light intensity of the light fixture (grid balancing) and/or charging the energy storage.
A brief surplus may also be taken up by a vertical farm according to the disclosure. Here, the light fixtures are operated with a higher intensity than what is provided for by the light recipe. The control unit has available the maximum illumination that a plant can accept without stress. In a first step, the illumination intensity (and hence the electricity consumption) is increased to this value.
However, it is also possible to briefly increase the intensity of the illumination above this threshold if a very large current supply is present and the grid power supply has to be relieved quickly (in order to take the “pressure” out of the power supply grid in real time; i.e., it is possible to also control the light fixtures in real time). Plants can withstand illumination that is too strong for a certain amount of time. In some embodiments/implementations, the stress on the plants is checked using a sensor for stress detection such that these are not stressed too strongly. A sensor for stress detection can be a fluorescence sensor, which measures the efficiency of the photosystem, or a cuvette for measuring gas exchange (CO 2 fixation in the plant), with the cuvette being attached at representative positions.
The sensors may provide data about the maximum capacity of the photosystem for the plants. Then the system can make decisions about how much electricity it can use for the lights (intensity or spectrum) without damaging the photosystem.
By measuring the activity of the photosynthesis and creating a light curve with regard to factors like temperature, and carbon dioxide level, the light level can slowly be increase up to the point where it is most comfortable to the plants. (Note: plants can adapt over time to higher light intensities) so a few days later maybe the comfortable zone could be higher or lower, depending on past illumination levels.
One way to prioritize certain products, is to implement current market prices for the crops. If possible, local prices would be the best
Since a vertical farm may also house different types of plants, the computing device can in some embodiments/implementations apply the brief stronger irradiation to those plants that are less susceptible to elevated illumination intensities.
Moreover, the computer device has access to information about what products are grown in the coming days and what light recipes are required to this end. The light recipes are associated with time-resolved energy consumption. In a conventional grid power supply, the light recipes would simply be run through.
Typical behaviors of the computing device appear to be:
the plants are illuminated with a lower photon flux and/or a different spectrum in the case of high energy costs. In exchange, a higher photon flux and/or a different spectrum can be made available at times with lower energy costs.
Vertical farms may also be operated predominantly at night, with the adaptations or control mechanisms described above also being carried out here on account of electricity price variations.
›SUMMARY OF THE DISCLOSURE · 73 of 73
The computing device checks the actual costs and predicted costs of the illumination profile at regular intervals. A new optimization of the illumination profile is undertaken if the deviation exceeds a set threshold.
8 th aspect of “Smart Grid”: The method for agriculture according to the 7 th aspect of “Smart Grid”, comprising the steps of recalculating the planned light intensity curve after the end of the brief electricity surplus and taking account of the previously increased light intensity profile on account of the grid balancing.
These brief phases of excess irradiation are then taken in account by the computing device when calculating the dynamic light recipes; i.e., phases of excess irradiation are compensated by phases of lower irradiation or by a reduction in the irradiation time or by a change in the irradiation spectrum. The term “dynamic” can thus relate both to a time-varying irradiation intensity (e.g., photon flux) and to a time-varying irradiation spectrum of the respective light recipe. Thus, irradiation components of spectral regions, for example blue to dark-red, can be changed over time and can be adapted to the selected energy options. The timescales for change or adaptation may be implemented in a second, minute, hour or day clock or longer, depending on how the energy supply or the energy costs change.
However, unlimited amounts of energy are not available at all times in a smart grid if limits are placed on the costs or if the intention is to profit from times of particularly low or negative prices. According to the disclosure, the light recipes are not simply left statically but the light recipes are made dynamic; i.e., the light recipe, in particular the intensity of the emitted light, is modified depending on the availability of the energy.
As a result of rendering the light recipes dynamic, an optimal use of cost-effective electricity for the operation of the plant light fixtures is possible. Moreover, the controlled agricultural system is configured to also act as an energy storage for the smart grid (grid balancing). To this end, provision is made of adapting the dynamic light recipes to brief electricity surpluses or deficits or to low or high electricity costs and/or of charging or discharging an energy storage.
When the farm has decided how much energy it could consume, it feedbacks the information back to the grid which can either accept or reject the offer (rejection e.g. in case surplus needs to be taken). The API may include a user identification, so that the power supplier directly knows who is making the offer and/or whom it is talking to.
When the modified power supply is applied, the effect on the plants is checked regularly with regards to thresholds prescribed by margins of the growth recipe i.e. to see if not too much stress in introduced on the plant. Light sensor is an example of a sensor, which could be used for verification, but also pH- and/or EC-sensors could be used to monitor water content if circulation is increased, or visual sensors for stress detection if only the spectrum rather than switching off the light are manipulated.
For the time being, it appears that the “smart grid” only provides tariffs, in the form of:
Time-based (time during the day, day during the week, season); Location-dependent (city/rural, degrees of separation or distance from core distribution network); Tier-bound (min/max energy demand of the customer); Charge type (fixed price, consumption-based, demand-based, etc.).
Therefore at the moment the smart grid can only react to the price conditions provided by the energy supplier without providing an active response—e.g. given the demand of particular crops in coming times and their associated growth recipes, the software can only figure out an optimal match to the available tariffs, i.e. plan the optimal growth settings.
An alternative to planning and reactive operation would be to buffer the energy in power banks at the time when prices are low and using that reserve when the prices are high. This could especially be used to store energy when the prices are negative. The stored electricity could then simply be sold in times of positive prices.
In conclusion, according to the disclosure, the control, as explained above, of the controlled agricultural system in a smart grid not only obtains economical advantages by an optimal use of more cost-effective current, instead the controlled agricultural system also acts as an energy buffer in a smart grid (grid balancing). These aspects are assisted as a result of rendering the light recipes dynamic.
Naturally, a controlled agricultural system connected to a smart grid power supply (smart grid) can also store energy, for example in batteries, flywheel energy storages and the
›Tables in the description — 7
| Species | Seed | Cutting | Vegetative | Reproductive |
|---|---|---|---|---|
| Cannabis | 100-300 | 75-150 | 300-600 | 600+ |
| Tomatoes | 150-350 | 75-150 | 350-600 | 600+ |
| Cucumbers | 100-300 | — | 300-600 | 600+ |
| Peppers | 150-350 | — | 300-600 | 600+ |
| 1 st Growth Recipe | Spectrum | |||
| Crop | Lactuca sativa ‘Diablotin’ | UV | 0 | |
| Light intensity | 240 μmol m −2 s −1 | Blue | 60 | |
| Photoperiod | 16 day/8 night | Green | 0 | |
| Temperature | 20° C. day/18° C. night | Hyper Red | 180 | |
| Humidity | 60-70% | Far Red | 0 | |
| Growth Cycle | 28 days | Warm White | 0 | |
| 2 nd Growth Recipe | Spectrum | |||
| Crop | ||||
| Ocimum basilicum | ||||
| UV | 10 | |||
| ‘Keira’ | ||||
| Light intensity | 300 μmol m −2 s −1 | Blue | 60 | |
| Photoperiod | 18 day/8 night | Green | 30 | |
| Temperature | 24° C. day/22° C. night | Hyper Red | 170 | |
| Humidity | 60-70% | Far Red | 0 | |
| Growth Cycle | 50 days | Warm White | 30 | |
| 3 rd Growth Recipe | Spectrum | |||
| Crop | ||||
| Cannabis sativa/indica | ||||
| UV | 5 | |||
| Light intensity | 330 μmol m −2 s −1 | Blue | 70 | |
| Photoperiod | 16 day/8 night | Green | 50 | |
| (for young plants) | Hyper Red | 200 | ||
| 12 day/12 night | ||||
| (for flowering) | ||||
| Temperature | 20 | Far Red | 5 | |
| 7° C. day/24° C. night | ||||
| Humidity | 60% | Warm White | 0 |
| DLI [mol/m 2 d] | 5 | 10 | 15 | 20 |
| T [° C.] | ||||
| 14 | 80 | 65 | 50 | 42 |
| 17 | 48 | 40 | 35 | 30 |
| 20 | 35 | 30 | 28 | 25 |
| 23 | 30 | 28 | 23 | 20 |
| 107.A | Acquiring and/or calculating unit and evaluation unit. |
| 107.B | Database of light recipes; energy evaluation and |
| assignment to light recipe. | |
| 107.C | Correlating light recipe to product. |
| 107.D | Presentation and communication of product |
| selection: energy consumption of light recipe or | |
| energy consumption per desired order process | |
| BS; selecting light recipe. | |
| 107.E | Customer order process of products based on ecologically rated |
| lighting and/or growing conditions | |
| 107.F | External control variables (ecology, environmental factors, etc.). |
| 107.G | Interface to FIG. 103. |
| 108.A | Database for light recipe(s). |
| 108.B | Control unit for the illumination unit/irradiation device. |
| 108.C | Actuating the light sources of an illumination unit. |
| 108.D | Light sources. |
| 108.E | Sensors for measuring light and radiation variables; M1. |
| 108.F | Control device: acquiring: measurement |
| variables, evaluation device, order. Additionally, | |
| customer-interactive modifications, also an automated | |
| order triggered by a manipulated variable being | |
| reached (measurements, order parameters). | |
| Determining the residual light amount, time | |
| duration of the irradiation or residual irradiation. | |
| 108.G | Evaluation device. |
| 108.H | Sensors and measurement device of plant |
| specific and/or surroundings-specific parameters | |
| with data acquisition and storage; M2. | |
| 108.I | Interface from FIG. 102. |
| 108.J | Presentation and communication of product |
| selection: energy of light recipe or energy | |
| for desired order process BS; selecting light recipe. | |
| 108.K | Customer order process of product and |
| energy-assessed light scenarios. Operator breeding | |
| and/or growing and/or raising control. | |
| 108.L | Customer information about product |
| status, delivery status, residual | |
| light amount, storage conditions etc. |
| 109.A | Receiving light recipe from a customer |
| and coupling to a plant product, | |
| illumination location and illumination unit. | |
| 109.B | Certification body. |
| 109.C | Database for certified light recipes. |
| 109.D | App for selection of light recipes for |
| growth product, and for selecting a | |
| provider or producer, and for triggering | |
| an order process, and for the interactive | |
| creation of a light recipe, and for capturing | |
| a customer measurement. App may | |
| also be interactive (other customers, user group). | |
| 109.E | Customer measurement (determination of active ingredients). |
| Building A | i | 1-n |
| Segments S | j | 1-m |
| Illumination unit B | k | 1-p |
| Light scenario L | x | 1-r |
| Time T | y | s |
| Integration time Delta-T | z | t |
| Energy consumption per data point EDP | ||
| Light recipe LR | e | 1-u |
| Order process B | w | 1-v |
| Effect values WW |
Claims as granted
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4 codes- A01G31/04
- A01G9/24
- G06Q10/0639
- G06Q50/02
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