Methods and algorithms for optimizing the application of residue-restricted crop protection products using variable rate application

Abstract

Described herein are methods and systems for generating instructions for a variable rate application of a crop protection material, including calculating a total dose of the crop protection material(s) that is allowed to be applied in a crop field such that the residue of the crop protection material(s) in a crop product grown in the crop field does not exceed a predefined MRL; adjusting the total dose according to a residue impact parameter; mapping the crop field into segments according to a pest distribution of one or more pests in each segment; calculating a dose of the crop protection material(s) that is estimated to be effective in controlling the pest(s) in each segment based on the pest distribution in the respective segment; calculating a variable rate application of the total dose of the crop protection material in the crop field based on the estimated dose for each segment; and outputting instructions for applying the crop protection material(s) in the crop field according to the variable rate application.

Description

[0001] Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 010,783, filed April 16, 2020, the contents of which are incorporated by reference in their entirety. BACKGROUND

[0003] The present invention, in some embodiments thereof, relates to applying crop protection material in a planted crop field, and, more specifically, but not exclusively, to applying crop protection material in a crop field according to a variable rate application plan.

[0004] Since the era of the agricultural revolution, harmful organisms (e.g., weeds, nematodes, mites, fungi, insects, disease pathogens, etc.) have posed challenges to agriculture.

[0005] Accordingly, various means, methods, and systems have been developed to control (e.g., eradicate, kill, incapacitate, repel, deter, suppress, limit, prevent, etc.) harmful organisms to prevent the harmful organisms from infecting farmlands and crops planted in these fields and / or competing with the crops for resources (e.g., water, soil, fertilizer, etc.) so as to cause harm or damage to the crops or to reduce the yield and / or quality of the crops.

[0006] One of the most effective means for controlling harmful organisms in modern agriculture is to apply various chemical and / or biological materials and substances in crop fields, such as herbicides, fungicides, pesticides, nematicides, insecticides, miticides, surfactants, etc. However, such chemical materials can have undesirable side effects, as residues of these chemical substances can be potentially dangerous, can remain in the crops, especially in crop products extracted from the crop fields, and can cause health risks when such products are consumed. SUMMARY

[0007] According to a first aspect of the present invention, there is provided a computer- implemented method of generating instructions for variable rate application of crop protection material, the method comprising:

[0008] - calculating a total dose of one or more crop protection materials allowed to be applied in a crop field such that residues of the crop protection material(s) in a crop product planted in the crop field do not exceed a predefined maximum residue limit (MRL).

[0009] - adjusting the total dose according to at least some of a plurality of residue- affecting parameters of the crop field.

[0010] - mapping the crop field into a plurality of sections according to a harmful organism distribution of one or more harmful organisms in each section of the plurality of sections.

[0011] - calculating a dose of the crop protection material estimated to be effective in controlling the pest(s) in each of the plurality of sections based on the pest distribution in the respective section.

[0012] - calculating a variable rate application of the total dose of the crop protection material in the crop field based on the estimated dose for each of the plurality of sections.

[0013] - outputting instructions for applying the crop protection material(s) in the crop field according to the variable rate application.

[0014] According to a second aspect of the invention, there is provided a system for generating instructions for a variable rate application of a crop protection material, the system comprising one or more processors executing code, the code comprising:

[0015] - code instructions for calculating a total dose of one or more crop protection materials allowed to be applied in a crop field such that the residue of the crop protection material(s) in a crop product planted in the crop field does not exceed a predefined MRL.

[0016] - code instructions for adjusting the total dose according to at least some of a plurality of residue affecting parameters of the crop field.

[0017] - code instructions for mapping the crop field into a plurality of sections according to a pest distribution of one or more pests in each of the plurality of sections.

[0018] - code instructions for calculating a dose of the crop protection material estimated to be effective in controlling the pest(s) in each of the plurality of sections based on the pest distribution in the respective section.

[0019] - code instructions for calculating a variable rate application of the total dose of the crop protection material in the crop field based on the estimated dose for each of the plurality of sections.

[0020] - code instructions for outputting instructions for applying the crop protection material(s) in the crop field according to the variable rate application.

[0021] According to a third aspect of the invention, there is provided a computer program product comprising computer readable program code for execution by one or more processors when retrieved from a non-transitory computer readable medium, the program code comprising code instructions for generating instructions for a variable rate application of a crop protection material by:

[0022] - calculating a total dose of one or more crop protection materials that is allowed to be applied in the crop field such that a residue of the crop protection material(s) in a crop product planted in the crop field does not exceed a predefined maximum residue limit (MRL).

[0023] - adjusting the total dose in dependence on at least some of a plurality of residue influencing parameters of the crop field.

[0024] - mapping the crop field into a plurality of sections in dependence on a pest distribution of one or more pests in each section of the plurality of sections.

[0025] - calculating a dose of the crop protection material(s) that is estimated to be effective to control the pest(s) in each section of the plurality of sections based on the pest distribution in the respective section.

[0026] - calculating a variable rate application of the crop protection material in the crop field based on the dose estimated for each section of the plurality of sections.

[0027] - outputting instructions for applying the crop protection material(s) in the crop field in dependence on the variable rate application.

[0028] In a further implementation form of the first aspect, the second aspect, and / or the third aspect, the instructions further define applying one or more crop protection materials in at least a subset of the plurality of sections in dependence on the variable rate application, the subset comprising sections selected from the plurality of sections such that a cumulative dose does not exceed the total dose.

[0029] In a further implementation form of the first aspect, the second aspect, and / or the third aspect, the subset comprises sections selected from the plurality of sections based on a ranking score such that the subset comprises a plurality of highest ranked sections of the plurality of sections having a cumulative dose that does not exceed the total dose, the ranking score being calculated for each section of the plurality of sections based on a respective pest distribution in the respective section.

[0030] In a further implementation form of the first aspect, the second aspect, and / or the third aspect, the instructions further define applying a plurality of crop protection materials separately in dependence on a respective variable rate application in case a plurality of crop protection materials is selected for application in one or more sections.

[0031] In an optional implementation form of the first aspect, the second aspect, and / or the third aspect, the one or more crop protection materials are selected in dependence on one or more of the pest(s) identified based on the pest distribution.

[0032] In a further implementation form of the first, second, and / or third aspects, each of the one or more harmful organisms is a member of the group consisting of weeds, nematodes, mites, fungi, insects, and disease pathogens.

[0033] In a further implementation form of the first, second, and / or third aspects, each of the one or more crop protection materials is a member of the group consisting of herbicides, fungicides, biocides, nematicides, insecticides, miticides, surfactants, and adjuvants.

[0034] In a further implementation form of the first, second, and / or third aspects, the plurality of residual impact parameters comprises a type of one or more of the crop protection material(s), a growth stage of the crop, an estimated biomass of the crop, an estimated residual from one or more previous crop protection material applications in the crop field, an estimated residual crop protection material estimated for one or more future crop protection material applications planned for the crop field, an organic matter (OM) content in the crop field, a type of one or more of the harmful organisms, a type of one or more crop protection materials previously applied in the crop field, and environmental conditions in a geographical area of the crop field.

[0035] In a further implementation form of the first, second, and / or third aspects, the harmful organism distribution is identified based on an analysis of one or more images of the crop field.

[0036] In a further implementation form of the first, second, and / or third aspects, the harmful organism distribution is identified based on an analysis of one or more past images of the crop field captured in one or more previous growth cycles.

[0037] In a further implementation form of the first, second, and / or third aspects, the harmful organism distribution is identified based on an analysis of one or more crop growth reports generated for the crop field.

[0038] In a further implementation form of the first, second, and / or third aspects, the harmful organism distribution is identified based on an analysis of sensory data captured by one or more sensors in the crop field.

[0039] In an optional implementation form of the first, second, and / or third aspects, the mapping the plurality of segments is further based on a zoning map of the crop field, the zoning map mapping the crop field into a plurality of zones based on one or more of a plurality of soil properties for each zone, the plurality of zone properties comprising soil properties, water properties, and topography properties.

[0040] In a further implementation form of the first, second and / or third aspect, the effective control reflects eradicating and / or driving off one or more of the (multiple) harmful organisms in the respective section by at least a predefined minimum percentage.

[0041] In a further implementation form of the first, second and / or third aspect, the effective control reflects limiting the impact of one or more of the (multiple) harmful organisms in the respective section to below a predefined maximum percentage of the yield of the crop.

[0042] In an optional implementation form of the first, second and / or third aspect, one or more machine learning models are applied to calculate the respective dose for one or more of the plurality of sections. The one or more machine learning models are trained to establish a correlation between a plurality of doses of one or more of the (multiple) crop protection materials and an effective control of a plurality of harmful organism distributions of one or more of the (multiple) harmful organisms.

[0043] In an optional implementation form of the first, second and / or third aspect, the total dose is calculated first, and then the variable rate application is calculated by:

[0044] - mapping the crop field into the plurality of sections based on the harmful organism distribution.

[0045] - calculating a respective dose for the (multiple) crop protection material in each section of the plurality of sections based on the harmful organism distribution in the respective section.

[0046] - calculating the variable rate application based on the dose estimated for each section of the plurality of sections.

[0047] - calculating the total dose such that the residue of the at least one crop protection material in the crop product planted in the crop field does not exceed a predefined MRL.

[0048] In an optional implementation form of the first, second and / or third aspect, the variable rate application and / or a part thereof is rejected if the cumulative dose of the respective doses of the plurality of sections exceeds the total dose.

[0049] Other systems, methods, features, and advantages of the present disclosure will be or become apparent to one with skill in the art upon examination of the following drawings and detailed description. It is intended that all such additional systems, methods, features, and advantages be included within this description, be within the scope of the present disclosure, and be protected by the accompanying claims.

[0050] Unless otherwise defined, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the application pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the application, exemplary methods and / or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.

[0051] Implementation of the method and / or system of embodiments of the application can involve performing or completing selected tasks manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of embodiments of the method and / or system of the application, several selected tasks could be implemented by hardware, by software or by firmware or by a combination thereof.

[0052] For example, hardware for performing selected tasks according to embodiments of the application could be implemented as a chip or a circuit. As software, selected tasks according to embodiments of the application could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In an exemplary embodiment of the application, one or more tasks according to exemplary embodiments of method and / or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, a data processor includes a volatile memory for storing instructions and / or data and / or a non-volatile storage, for example, a magnetic hard disk and / or removable media, for storing instructions and / or data. Optionally, a network connection is provided as well. A display and / or a user input device such as a keyboard or mouse are optionally provided as well. BRIEF DESCRIPTION OF DRAWINGS

[0053] Some embodiments of the application are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the application. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the application can be practiced.

[0054] In the drawings:

[0055] Figure 1 is a flowchart of an exemplary process of generating instructions for variable rate application of crop protection material in a crop field mapped into a plurality of segments based on pest distribution, in accordance with some embodiments of the application;

[0056] Figure 2 is a schematic diagram of an exemplary system for generating instructions for variable rate application of crop protection material in a crop field mapped into a plurality of segments based on pest distribution, in accordance with some embodiments of the application; and is a flowchart of an exemplary process of generating instructions for variable rate application of crop protection material in a crop field mapped into a plurality of segments based on pest distribution, in accordance with some embodiments of the application;

[0057] Figure 3A and Figure 3B is a schematic illustration of an exemplary crop field based on the plurality of zones being mapped for variable rate application of crop protection material based on the pest distribution identified in each zone according to some embodiments of the application. DETAILED DESCRIPTION

[0058] The present application, in some embodiments thereof, relates to application of crop protection material in a crop field and, more specifically, but not exclusively, to application of crop protection material in a crop field according to a variable rate application plan.

[0059] Modern agriculture uses a wide array of chemical materials and substances that are designed and configured to control pests, e.g., eradicate, kill, incapacitate, repel, deter, suppress, limit, and / or otherwise prevent pest infestation of a field, its soil, and / or one or more crops planted in a crop field, e.g., a field, orchard, garden, plantation, vineyard, etc.

[0060] Pests can include, for example, weeds, nematodes, mites, fungi, insects, disease pathogens, etc., and thus the chemicals can include a variety of crop protection materials that can be selected to effectively eradicate a particular pest identified in a crop field, e.g., herbicides, fungicides, pesticides, nematicides, insecticides, miticides, surfactants, etc. The crop protection material can include one or more substances or mixtures of substances intended for the control, prevention, destruction, repulsion, or mitigation of one or more pests and intended for use as plant regulators, defoliants, and / or desiccants.

[0061] However, residues of crop protection materials, metabolites thereof, or other degradation products can remain and contaminate the crop, especially the crop product extracted (harvested, picked, collected, etc.) from the crop field. Since these crop protection materials and / or metabolites thereof or other degradation products thereof can be potentially hazardous, the remaining residues can pose one or more health risks when the crop product is consumed. To ensure that the residue levels (amounts, concentrations, percentages, etc.) of crop protection materials in the crop end (consumer) product are within a safe range, maximum residue limits (MRLs) can be predefined and enforced accordingly to set acceptable non-harmful residue levels of each crop protection material and / or combinations of crop protection materials in the crop product. The maximum residue levels defined by the MRLs can further include one or more metabolites and / or other degradation products of the (multiple) crop protection materials that can reach the crop, especially the crop product, directly, via the plant, via the soil in which the crop is planted, etc., in addition to the direct residues of the crop protection materials. The predefined MRLs defining the maximum residue amounts allowed on the crop product can be defined, set, and / or enforced by one or more health and / or regulatory agencies. Crop product labels will typically indicate their MRLs in order to convey this information to the end customer throughout the supply chain and / or portions thereof.

[0062] Accordingly, the total dose (amount) of the one or more crop protection materials and / or combinations of multiple such crop protection materials allowed to be applied in a particular crop field during a certain growing cycle can be derived from the MRLs predefined for the crop end product extracted from the particular crop field. In other words, the total dose of the (multiple) crop protection materials allowed to be applied in the particular crop field must be such that the cumulative residue of the (multiple) crop protection materials in the crop product does not exceed the predefined MRLs.

[0063] In particular, the total allowed dose can be derived from the average residue of the crop product of the crop protection material(s) such that the average residue of the crop product of all crops does not exceed the predefined MRL. This can be applicable, inter alia, to crop products extracted from the crop field that are mixed together after extraction. Such crops can include various crops and plant families, including field crops, vegetable crops, fruits, semi-perennial crops, and perennial crops, to name a few. These crops can include, for example, cereals (e.g., wheat, barley, rye, oats, rice, sorghum, and related crops); beet (e.g., sugar beet and fodder beet); pome, stone, and soft fruit (e.g., apples, pears, plums, peaches, almonds, cherries, strawberries, raspberries, and blackberries); leguminous plants (e.g., beans, vetches, peas, soybeans); oil crops (e.g., oilseed rape, mustard, olives, sunflowers, coconut palms, castor oil plants, cocoa beans, and groundnuts); gourd crops (e.g., marrows, cucumbers, and melons); fiber plants (e.g., cotton, flax, hemp, and jute); citrus fruits (e.g., oranges, lemons, grapefruits, and mandarins); vegetables (e.g., spinach, lettuce, asparagus, cabbages, carrots, onions, tomatoes, potatoes, and bell peppers); lauraceae (e.g., avocados, cinnamoms, and camphors); plants such as maize, tobacco, nuts, coffee, sugar cane, tea, grapevines, hops, bananas, and natural rubber plants, etc. The crops can further include ornamental plants such as flowers, shrubs, broad-leaved trees, and / or evergreens (such as conifers, etc.).

[0064] Furthermore, the residue level can be influenced by one or more parameters of the crop field (e.g., soil, water, topography), the crop protection material applied to the crop field during the entire growth cycle of the crop, environmental conditions (e.g., climate, weather), etc., which are hereinafter collectively referred to as residue influencing parameters.

[0065] According to some embodiments of the present application, there are provided systems, methods, and computer program products for generating instructions for variable rate application of one or more crop protection materials in a crop field mapped into a plurality of segments based on pest distribution in order to apply an effective dose of the crop protection material in different sub-zones or segments of the crop field while not exceeding a total (aggregate) dose of the crop protection material allowed to be applied in the entire crop, which is derived from a predefined MRL for the crop product extracted from the crop field.

[0066] The total dose of the one or more crop protection materials selected for application in the crop field is first calculated based on a predefined MRL for the crop product ultimately extracted from the crop field (at the end of the growing cycle). The total dose is the maximum dose of the crop protection material(s) allowed to be applied (sprayed, sprinkled, spread, etc.) across the entire crop field such that the residue of the crop protection material(s) in the crop product does not exceed the predefined MRL. In particular, the total dose can be the maximum dose of the crop protection material(s) allowed to be applied in the crop field such that the residue of the crop protection material(s) in the product extracted from the entire crop field does not exceed, on average, the predefined MRL.

[0067] The residue level of the crop protection material(s) in the crop product can primarily depend on the amount of the crop protection material(s) applied on the crop and the disintegration rate or decay time of the applied crop protection material(s). Thus, the expected residue level can be estimated based on the amount of the crop protection material(s) sprayed (applied) in the crop field and the time of product extraction (harvesting).

[0068] However, since the residue level can be influenced by one or more residue influencing parameters, the total dose can be adjusted according to the residue influencing parameters applicable to the crop field. For example, the total dose can be influenced by the type of the crop protection material(s) selected for application in the crop field, since different crop protection material(s) can have different residue properties (e.g. decay time, disintegration rate, etc.) and / or different residue influence. In another example, the total dose can be influenced by one or more other (past and / or future) applications of the crop protection material(s) in the crop field, especially in the current growing cycle, since the cumulative residue level of the crop protection material(s) in the crop product must not exceed the MRL. In another example, the total dose can be influenced by one or more environmental and / or weather conditions, for example, overcast and rainy weather can contribute to an increase in the wash-off of the residue in the crop and / or crop product, which can decrease the residue level.

[0069] The crop field can then be divided into a plurality of segments based on the pest distribution obtained for the crop field such that the pest distribution is substantially uniform in each segment. Alternatively, the plurality of segments can be drawn according to one or more pest distribution scales (e.g. percentage of infected crop plants, etc.) such that the pest distribution in each segment is within a predefined pest distribution range, for example, 0-10%, 11-20%, 21-30%, 31-40%, and so on.

[0070] The pest distribution in the crop field can be mapped based on analysis of sensory data captured by one or more sensors to depict the crop field. For example, the sensory data can include one or more images of the crop field, which can be analyzed to identify visual evidence and / or indications of pests, such as presence of weeds, potential infestation and / or damage of crop plants indicative of one or more pests, and / or the like. In another example, the sensory data can include a spectral plot of the crop field illuminated with one or more light sources (e.g., infrared (IR), ultraviolet (UV), and / or the like). The spectral response of one or more pests to the illumination can be different from the spectral response of the crop and / or the crop field, and thus the spectral plot can be analyzed to identify such pest(s), such as weeds, insects, changes and / or indications in the crop plants, and / or the like. Optionally, at least a portion of the pest distribution can be derived from sensory data captured for a sample (e.g., a zone, a portion, and / or the like) of the crop field, which can be manipulated (e.g., extrapolated, interpolated, and / or the like) to estimate the pest distribution in other zones of the crop field.

[0071] The pest distribution and / or portions thereof can be further derived from one or more reports, such as a survey report, a reconnaissance report, and / or the like generated for the crop field, which can include information related to one or more pests, particularly information related to the distribution of the pest(s). Further, at least some of the pest distribution can be derived from one or more reports generated for one or more samples (e.g., zones, portions, and / or the like) of the crop field, which can be manipulated to estimate the pest distribution in other zones of the crop field.

[0072] Optionally, the pest distribution can be based on past sensory data captured in the crop field and / or one or more reports including pest distribution information generated for the crop field during one or more previous growth cycles.

[0073] Optionally, dividing the crop field into a plurality of sections is further based on a regional map generated for the crop field according to one or more attributes (e.g., soil attributes, water attributes, and / or topographical attributes) identified, measured, and / or calculated for one or more regions of the crop field.

[0074] A respective dose of the one or more selected crop protection materials can then be computed for each of the plurality of segments of the crop field based on the pest distribution identified in each segment. The respective dose is a dose that is estimated to be effective in controlling the pest(s) in the respective segment as reflected by the pest distribution identified in the respective segment (e.g., eradicate, repel, etc.). Effective control of the pest(s) can be defined according to one or more criteria. For example, effective control can reflect that a predefined minimum estimated percentage of the pest(s) in the respective segment are estimated to be eradicated and / or repelled, e.g., 70%, 80%, 90%, 95%, etc. In another example, effective control can reflect that the impact of the pest(s) on crop yield in the respective segment is estimated to be less than a predefined maximum percentage, e.g., 30%, 20%, 10%, 5%, etc.

[0075] Optionally, one or more machine learning (ML) models can be used to compute effective doses of the crop protection material(s) for one or more segments using artificial intelligence (AI). The ML models can be trained and learned to establish a correlation between application parameters of the crop protection materials (e.g., type, dose, time of application, etc.) and their impact on pests (i.e., their effectiveness in controlling pests (e.g., percentage of eradication and / or repelling, impact on percentage of yield, etc.).

[0076] A variable rate application of the total dose (or a portion thereof) of the crop protection material(s) for application in the crop field can then be computed based on the doses computed for each segment. Thus, the variable rate application can define varying application of the crop protection material(s) in at least some segments of the crop field according to the respective doses computed for these segments.

[0077] Optionally, the variable rate application is computed so that the selected crop protection material(s) are not applied at all in one or more sections of the crop field. One or more sections of the crop field can not be treated, for example, to avoid exceeding the total dosage allowed to be applied in the crop field, at the cost of the yield of the crop possibly being reduced due to the (multiple) pests in the untreated section(s) not being controlled. In another example, if it is estimated that the selected crop protection material(s) can not be effective in controlling the (multiple) pests in one or more sections, and it can be more effective to apply one or more different crop protection materials in that section(s), the section(s) can not be treated.

[0078] Optionally, the variable rate application is computed so that the selected crop protection material(s) are not applied at all in one or more sections of the crop field. One or more sections of the crop field can not be treated, for example, to avoid exceeding the total dosage allowed to be applied in the crop field, at the cost of the yield of the crop possibly being reduced due to the (multiple) pests in the untreated section(s) not being controlled. In another example, if it is estimated that the selected crop protection material(s) can not be effective in controlling the (multiple) pests in one or more sections, and it can be more effective to apply one or more different crop protection materials in that section(s), the section(s) can not be treated.

[0079] Instructions for applying the crop protection material(s) in the crop field according to the computed variable rate application can be generated. The variable rate application instructions can be used by one or more ground and / or aerial, autonomous and / or manually operated applicator systems, e.g., systems, machines, vehicles, equipment, devices configured, adjusted and / or operated to apply (spray) the crop protection material(s) in the crop field. In particular, the instructions can be used by real-time configured, adjusted and / or operated applicator systems to control and adjust the rate (e.g., amount, volume, flow, etc.) of application (spraying) of the crop protection material(s) at any given time, thereby supporting the variable rate application according to the instructions.

[0080] While one or more of the crop protection material(s) can be selected based on past learned and practiced agricultural practices, conventions, and / or knowledge for application in the crop field, optionally, one or more of the crop protection material(s) can be selected based on the type of pest(s) identified in the crop field based on the analysis of the crop field.

[0081] Optionally, after partitioning based on pest distribution, the effective dose can be first computed for each segment of the crop field. The variable rate application of the crop protection material(s) for application in the segments can then be computed based on the respective effective dose computed for each segment. The generated plan including instructions for the variable rate application can be approved if the cumulative dose of all effective doses does not exceed the total dose computed for the crop field, and rejected if the cumulative dose exceeds the total dose. Optionally, in case the cumulative dose exceeds the total dose, a subset of the plurality of segments can be selected for application of the crop protection material(s) according to the variable rate application.

[0082] The variable rate application of the crop protection material(s) can bring significant benefits and advantages compared to existing methods and systems for application of crop protection materials.

[0083] First, some existing methods can apply the total dose of the crop protection material(s) at a constant (fixed) rate across the entire crop field. Since the pest distribution can vary among different segments of the crop field, applying the crop protection material(s) at a constant rate can result in over-application of the crop protection material(s) in segments with low pest distribution, and possibly ineffective doses due to under-application in segments with high pest distribution. In contrast, the variable rate application(s) can ensure that each segment can be applied with an effective dose specifically computed for the respective segment based on the pest distribution identified in the respective segment, while complying with the limit on the average residue level derived from the pre-defined MRL. Reduced crop protection material(s) can be applied to segments with low pest distribution and optionally no crop protection material(s) applied, while increased doses of the crop protection material(s) can be applied to segments with high pest distribution to effectively eradicate the pests in these segments.

[0084] Furthermore, the total dose of the crop protection material(s) allowed for a crop field is limited to comply with predefined MRLs, especially for the crop(s) extracted from the crop field. Thus, applying the limited total dose at a constant rate to the crop field can result in a reduced application dose in each segment, leading to a possible insufficient dose of the crop protection material(s) applied in segments of the crop field with a high pest distribution, thus failing to effectively eradicate the pests in these segments. On the other hand, variable rate application can significantly increase the utilization of the limited total dose, as a significantly reduced dose of the crop protection material(s) can be applied to segments with a low pest distribution and optionally not at all, thus preserving an increased volume of the crop protection material(s) to be applied to segments requiring an increased dose.

[0085] Furthermore, as modern agriculture is continuously evolving and moving towards precision agriculture, many agricultural fields have already deployed means such as systems, devices and methods to support sensory data acquisition, imaging, field surveys, mapping, etc. of crop fields. Thus, variable rate application can leverage such existing means to map and divide the crop field without further deployment of imaging and mapping devices and / or infrastructure.

[0086] Additionally, by analyzing the crop field to identify the type and distribution of the pest(s) in the crop field, the most suitable crop protection material(s) can be selected to improve the effectiveness of eradicating the pest(s) while potentially reducing the dose of the crop protection material(s) applied throughout the crop field.

[0087] Furthermore, applying the ML model(s) and using AI to calculate the dose of the crop protection material(s) to be applied in a segment can improve the accuracy of applying an effective dose only where needed, without the occurrence of underdosing, which can significantly slow down the development of resistance of pests.

[0088] Before one or more embodiments of the application are explained in detail, it is to be understood that the application is not limited in its application to the details of construction and the arrangements of the components and / or methods set forth in the following description and / or illustrated in the following drawings. The application can be implemented or carried out in other embodiments or by other means.

[0089] As those skilled in the art will appreciate, aspects of the present application can be embodied as a system, method, or computer program product. Accordingly, aspects of the present application can take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that can all generally be referred to herein as a "circuit," "module" or "system." Furthermore, aspects of the present application can take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

[0090] Any combination of one or more computer readable medium can be used. The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch cards or raised structures in

[0091] Computer program code embodied on a computer readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0092] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The computer readable program instructions can be further executed as one or more network and / or cloud-based applications that can be connected to the Internet or disconnected from the Internet in real-time. The network can include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. Network interface cards or network adapters in each computing / processing device receive the computer readable program instructions from the network and forward the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0093] Computer readable program instructions for carrying out operations of the present application can be written in any combination of one or more programming languages, such as assembly language, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or in any combination of source code or object code written in one or more programming languages including object oriented programming languages such as Smalltalk, C++, or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

[0094] The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry to perform aspects of the present application.

[0095] Various aspects of the present application are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0096] The diagrams in the figures illustrated the architectures, functions, and operations of the examples of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart and / or block diagrams can represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical functions ("instructions"). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[0097] Referring now to the drawings, Figure 1 is a flowchart of an exemplary process for generating instructions for variable rate application of a crop protection material in a crop field mapped into a plurality of zones based on pest distribution according to some embodiments of the present disclosure.

[0098] The exemplary process 100 can be executed to generate a plan (prescription) comprising instructions for applying one or more crop protection materials in a crop field (i.e., a field of land where one or more crops are grown, such as a tillable field, orchard, garden, plantation, vineyard, etc.) in a manner that is applied at a variable rate.

[0099] The variable rate application is calculated to apply an effective dose of the crop protection material(s) in different sub-zones or zones of the crop field while the residue of the crop protection material(s) in the crop, particularly the crop product, does not exceed a particular MRL threshold.

[0100] Reference is also made to Figure 2 is a schematic diagram of an exemplary system for generating instructions for variable rate application of a crop protection material in a crop field mapped into a plurality of zones based on pest distribution according to some embodiments of the present disclosure. The exemplary crop protection material computing system 200 (e.g., a computer, a server, a computing node, a cluster of computing nodes, etc.) can be deployed to execute processes such as the process 100 for generating instructions for applying one or more crop protection materials in a crop field in a manner that is applied at a variable rate.

[0101] The crop protection material computing system 200 can include an input / output (I / O) interface 210, a processor(s) 212, and a storage device 214 for program code storage and / or data storage.

[0102] The I / O interface 210 can include one or more wired and / or wireless interfaces, such as a universal serial bus (USB) interface, a serial interface, a radio frequency (RF) interface, a Bluetooth interface, and the like. The I / O interface 210 can further include one or more network and / or communication interfaces for connecting to a network 206 including one or more wired and / or wireless networks, such as a local area network (LAN), a wireless local area network (WLAN), a wide area network (WAN), a metropolitan area network (MAN), a cellular network, the Internet, and the like.

[0103] The crop protection material computing system 200 can use the I / O interface 210 to output plans and / or prescriptions including instructions for variable rate application of one or more of the crop protection material(s) in the crop field 204 (e.g., a field, orchard, garden, plantation, vineyard, and the like). For example, the instructions can be computed and provided to one or more applicator systems 202 configured to apply the crop protection material(s) in the crop field 204, e.g., spraying, sprinkling, spreading, and the like, hereinafter collectively referred to as spraying. In particular, each applicator system 202 can be configured, adjusted, and / or operated in real-time to control and adjust the amount, volume, and / or flow of the crop protection material for each spray so as to support variable rate application in accordance with the instructions.

[0104] The applicator system 202 can include ground and / or aerial unmanned autonomous and / or manually operated systems, such as systems, machines, vehicles, devices, apparatuses, and the like. For example, the applicator system 202 can include one or more manually operated ground vehicles, such as a tractor 202A towing a spray trailer including one or more tanks containing one or more crop protection materials and configured to spray each crop protection material at a variable rate. In another example, the applicator system 202 can include one or more autonomous ground vehicles and / or systems, such as an automated spray system that can be deployed, moved, and maneuvered in the crop field 204. The automated spray system can be connected to one or more reservoirs containing one or more crop protection materials and can be further configured to spray each crop protection material at a variable rate. In another example, the applicator system 202 can include one or more manually operated aerial vehicles, such as a helicopter 202B configured to carry one or more tanks containing one or more crop protection materials and further configured to spray each crop protection material at a variable rate. In another example, the applicator system 202 can include one or more autonomous aerial vehicles, such as unmanned aerial vehicles (UAVs), drones, and the like, configured to carry one or more tanks containing one or more crop protection materials and further configured to spray each crop protection material at a variable rate.

[0105] The crop protection material calculation system 200 can further communicate with one or more remote networked resources 230, e.g., a client operated by a user for controlling the task management system 200, computing resources, storage resources, databases, services, cloud resources, etc., via the I / O interface 210, especially over a network.

[0106] The processor(s) 212 (homogenous or heterogeneous) can include one or more processors arranged for parallel processing, as a cluster and / or as one or more multi-core processors. The storage 214 can include one or more non-transitory persistent storage devices, e.g., read-only memory (ROM), flash memory arrays, hard drives, etc. The storage 214 can also include one or more volatile devices, e.g., random access memory (RAM) components, cache memory, etc. The storage 214 can further include one or more network storage resources, e.g., storage servers accessible via the network interface 210, network accessible storage (NAS), network drives, cloud storage, etc.

[0107] The processor(s) 212 can execute one or more software modules, e.g., processes, scripts, applications, agents, utilities, tools, etc., each including a plurality of program instructions stored in a non-transitory medium (program storage), such as the storage 214, and executed by one or more processors, such as the processor(s) 212. The processor(s) 212 can further include, integrate, and / or utilize one or more hardware modules (elements integrated in and / or utilized by the task management system 200, e.g., circuitry, components, integrated circuits (ICs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), etc.

[0108] The processor(s) 212 can thus execute one or more functional modules, e.g., the crop protection material calculator 220 for performing the process 100 using one or more software modules, one or more hardware modules, and / or a combination thereof.

[0109] Optionally, the crop protection material calculation system 200, especially the crop protection material calculator 220, can be implemented as one or more cloud computing services, e.g., infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), etc., deployed on one or more cloud computing platforms, e.g., Amazon Web Services (AWS), Google Cloud, Microsoft Azure, etc.

[0110] As shown in 102, the process 100 begins with the crop protection material calculator 220 calculating a total (aggregate) dose (amount) of one or more crop protection materials (e.g., herbicides, fungicides, pesticides, nematicides, insecticides, miticides, surfactants, etc.) selected for application in the crop field 204. Such crop protection materials can include, for example, glufosinate, glyphosate, mancozeb, chlorothalonil, propiconazole, linuron, iprodione, etc.

[0111] The crop protection material(s) can be selected to control (e.g., eradicate, kill, incapacitate, repel, deter, suppress, limit, and / or otherwise prevent) one or more pests (e.g., weeds, nematodes, mites, fungi, insects, disease pathogens, etc.) from infesting the crop field 204, its soil, and / or one or more crops planted in the crop field 204 (e.g., farmland, orchard, garden, plantation, vineyard, etc.).

[0112] The total dose is the maximum dose of the crop protection material(s) allowed to be applied in the crop field 204. The allowed total dose can be derived from one or more MRLs pre-defined by regulations, directives, conventions, and / or guidelines, defined for the crop field 204, and / or applicable to the crop field such that the residue of the crop protection material(s) on the product(s) of the crop(s) extracted (harvested, picked, collected, etc.) from the crop field 204 does not exceed a certain limit. Residues of the crop protection material(s) can pose one or more health risks when the crop product(s) are consumed, and thus the MRLs are pre-defined to prevent the product(s) from being contaminated with potentially dangerous residues.

[0113] In particular, the crop protection material calculator 220 can calculate the total allowed dose based on the average residue of the crop protection material(s) in the crop product such that the average residue of all of the crop product does not exceed the pre-defined MRL. This is especially applicable to crop products, such as wheat, rice, etc., that are mixed together after being extracted from the crop field.

[0114] The crop protection material calculator 220 can calculate the total dose based on the estimated residue of the crop protection material(s) on the crop product, which mainly depends on the amount of the crop protection material(s) applied (sprayed) on the crop and the disintegration rate or decay time of the applied crop protection material(s).

[0115] As shown in 104, the crop protection material calculator 220 can adjust the total dose of the selected crop protection material(s) according to one or more residue-affecting parameters applicable to the crop field 204, which can affect and / or impact the residue level of one or more of the crop protection material(s) in the crop product(s).

[0116] The residual impact parameters can relate to attributes of the crop field 204 itself that can affect the residual level of the crop protection material(s) that affect the crop product(s), such as the soil type in the crop field 204, the OM content in the crop field 204, the absorption parameters of the soil, and the like. For example, a soil type characterized by high absorption can reduce the residual level of the crop protection material(s) that can contaminate the crop product, while a soil type characterized by low absorption can increase the residual level of the crop protection material(s). In another example, a high OM content can reduce the residual level of the crop protection material(s) that can contaminate the crop product, while a low OM content can increase the residual level of the crop protection material(s).

[0117] The residual impact parameters can also relate to attributes of one or more of the crop(s) planted in the crop field 204, such as the type of the crop(s), the growth stage of the crop, the estimated biomass of the crop(s) (and, in particular, the crop product(s)), and the like. Each of these crop attributes can naturally affect the residual amount and / or level of the crop protection material(s) associated with the crop product, which can be expressed in the aggregate form of the crop product, in units of the crop product (e.g., per kilogram, per pound, and the like), in items of the crop product (e.g., per fruit, and the like). For example, a high estimated biomass can reduce the residual level of the crop protection material(s) per unit and / or per item of the crop product, while a low estimated biomass can increase the residual level of the crop protection material(s) per unit and / or per item of the crop product. In another example, a short remaining time until the crop product is extracted (e.g., harvested, picked, and the like) from the crop field 204 can reduce the time for the crop protection material(s) to exit (e.g., disintegrate, evaporate, be washed away, and the like) the crop product, which can increase the residual level of contamination of the crop product. Conversely, a long remaining time until the crop product is extracted from the crop field 204 can increase the time for the crop protection material(s) to exit the crop product, which can reduce the residual level in the crop product. Moreover, if the crop protection material(s) are applied during the pre-emergence stage of the final crop product (e.g., fruit, flower, and the like), the residual level of contamination of the crop product can be further reduced.

[0118] The residue impact parameter can also relate to properties of one or more of the crop protection material(s) selected for application in the crop field 204, such as the type of identified pest(s) in the crop field 204, the type of crop protection material, the disintegration parameter of the crop protection material, the evaporation parameter of the crop protection material, and the like. For example, a crop protection material that disintegrates and / or evaporates quickly can reduce the residue level of the crop protection material(s) that can contaminate the crop product, while a crop protection material that disintegrates and / or evaporates slowly can increase the residue level of the crop protection material(s) that can contaminate the crop product. Since the type of pest(s) can dictate, at least in part, the selection of the type and / or dosage of the crop protection material(s) applied in the crop field 204, the type of pest can also indirectly affect the residue level of the crop protection material(s) that can contaminate the crop product.

[0119] The residue impact parameter relating to the crop protection material properties can further relate to properties of one or more of the crop protection material(s) that were applied in the crop field 204 during the current growing cycle and / or that are planned to be applied in the crop field 204 during the current growing cycle. Residues of the crop protection material(s) that can contaminate the final crop product can accumulate from multiple applications of one or more crop protection materials on the crop(s) in the crop field 204 during the same growing cycle. Thus, the total dosage calculated for application in the crop field 204 must take into account residues from previous application(s) and / or future application(s) of one or more crop protection materials that should not exceed the MRL defined for the crop(s) in the crop field 204.

[0120] The residue impact parameter can further relate to one or more environmental conditions associated with the crop field 204, i.e., environmental conditions applicable to the geographic region of the crop field 204, such as the time of year, typical temperature, typical humidity, predicted rainfall, and the like. For example, frequent rainfall in the crop field 204 can wash away more residues of the crop protection material(s), thereby reducing the residue level of the crop protection material(s) that can contaminate the crop product(s), while limited rainfall can increase the residue level of the crop protection material(s) on the crop product(s). In another example, many sunny days in the geographic region of the crop field 204 can help increase disintegration and / or evaporation of residues of the crop protection material(s) that can contaminate the crop product(s), while few or even no sunny days in the geographic region of the crop field 204 can decrease disintegration and / or evaporation of residues of the crop protection material(s).

[0121] As shown in 106, the crop protection material calculator 220 can map the crop field 204 into a plurality of sections according to the distribution of one or more pests identified in each section of the crop field 204. The pest distribution can be represented by, for example, volume, density, concentration, and / or the like. One or more methods, techniques, and / or algorithms can be used to map and identify the pest distribution.

[0122] According to some embodiments, the pest distribution can be mapped and identified by analyzing sensory data depicting the crop field 204 captured by one or more sensors deployed for monitoring the crop field 204. Optionally, at least a portion of the pest distribution can be derived from sensory data captured for a sample (e.g., section, portion, and / or the like) of the crop field 204, which can be manipulated (e.g., extrapolated, interpolated, and / or the like) to estimate the pest distribution in other sections of the crop field 204. For example, the sensory data can include one or more images of the crop field 204 captured by one or more imaging sensors (e.g., cameras, video cameras, infrared sensors, thermal imaging sensors, and / or the like) deployed and configured to monitor the crop field 204. The pest distribution can thus be identified by analyzing the image(s) of the crop field 204 using one or more image processing and computer vision methods, techniques, and / or algorithms to identify one or more pests that can potentially harm and / or inhibit the growth of one or more crops planted in the crop field 204. In particular, the image(s) can be analyzed to identify visual evidence and / or indications of the presence of one or more pests in the crop field 204. For example, the image(s) can be analyzed to identify visually detectable weeds in one or more sections of the crop field 204. Further, based on the analysis, the type or species of one or more detected weeds can be identified. In another example, the image(s) can be analyzed to identify one or more visual changes and / or signs in the crop plants planted in the crop field 204 that can be indicative of infection and / or injury by one or more pests (e.g., nematodes, mites, fungi, insects, disease pathogens, and / or the like that infect the crop plants). The image(s) can be further analyzed to identify an estimated type or species of the pest(s) present in the crop field based on visual changes and / or signs typical of the pest(s).

[0123] In another example, the sensory data can include one or more spectral maps of the crop field 204 illuminated with one or more light sources (e.g., infrared (IR), ultraviolet (UV), etc.). The spectral response of one or more pests to the illumination can be different from the spectral response of the crop plants and / or the crop field 204, and thus the spectral map(s) can be analyzed to identify such pest(s), e.g., weeds, insects, changes in the crop plants, and / or signs of infestation, etc. Moreover, based on the analysis of the spectral map(s), the type or species of one or more detected weeds can be identified.

[0124] The sensory data depicting the crop field 204 can be captured by one or more ground, aerial, and / or space-based systems, vehicles, and / or devices operating to traverse the crop field 204 and capture data, e.g., images, spectral data, etc., of the crop field 204. For example, one or more images of the crop field 204 can be captured by one or more imaging sensors mounted on one or more satellites passing over the crop field 204. In another example, one or more images and / or spectral maps of the crop field 204 can be captured by one or more imaging sensors mounted on one or more autonomous and / or manually operated aerial vehicles (e.g., UAVs, drones, aircraft, etc.) operating to fly over the crop field 204. In another example, one or more images and / or spectral maps of the crop field 204 can be captured by one or more imaging sensors mounted on one or more autonomous and / or manually operated ground vehicles operating to drive in, around, and / or near the crop field 204.

[0125] Optionally, one or more trained machine learning (ML) models can be applied to the sensory data to identify one or more pests in the crop field 204. The ML model(s) (e.g., neural networks, support vector machines (SVMs), etc.) can be trained using one or more training data sets including sensory data (e.g., images, spectral maps, etc., of the crop field infected with one or more pests) in one or more supervised and / or unsupervised training sessions. Thus, the ML model(s) can learn, adapt, and evolve to establish a correlation between visual features associated with one or more pests (e.g., weed appearance, signs of infestation of plants, etc.) and the corresponding pest(s). In another example, the ML model(s) can learn, adapt, and evolve to establish a correlation between spectral responses associated with one or more pests and the corresponding pest(s).

[0126] According to some embodiments, the crop field 204 can be mapped into segments based on an analysis of one or more crop growth reports, scouting reports, and / or investigations generated for a current growth cycle and / or one or more previous growth cycles in the crop field 204. One or more of the report(s) can include pest distribution information that can be analyzed to map the crop field 204 into segments according to the pest distribution recorded in the report(s). The report(s) can be stored in one or more remote networked resources 208 that can be accessed and retrieved by the crop protection material calculator 220 via the network 206. Further, at least some of the pest distribution can be derived from one or more reports generated for one or more samples (e.g., zones, portions, etc.) of the crop field 204, for example, which can be manipulated to estimate the pest distribution in other zones of the crop field 204.

[0127] The crop protection material calculator 220 can divide the crop field 204 into segments such that the pest distribution is substantially uniform in each segment. Thus, a high pest distribution in a segment can indicate that the volume, density, and / or concentration of the respective pest in the respective segment is greater, while a low pest distribution in a segment can indicate that the volume, density, and / or concentration of the respective pest in the respective segment is lower (smaller). Alternatively, the crop protection material calculator 220 can divide the crop field 204 into segments according to one or more pest distribution scales (e.g., percentage of infected crop plants, etc.). In such embodiments, the crop protection material calculator 220 can generate segments having a pest distribution within a predefined pest distribution range, for example, 0-10%, 11-20%, 21-30%, 31-40%, and so on.

[0128] This means that the crop protection material calculator 220 can identify the distribution of the pest(s) in the crop field 204 and can divide the crop field 204 into segments according to the identified pest distribution in each segment. For example, adjacent zones of the crop field 204 that are identified as having substantially similar pest distribution can be divided together. In another example, the crop field 204 can be divided into segments arbitrarily and / or based on one or more attributes of the segments, and each segment can be associated with a respective pest distribution.

[0129] Optionally, the crop protection material calculator 220 can divide the crop field 204 into multiple sections based on one or more regional maps of the crop field 204, which are plotted as multiple regions. The regional maps of the crop field 204 can be based on one or more soil properties for each region, such as soil properties, water properties, topographic properties, etc. Soil properties that can be measured in the regions of the crop field 204 using one or more sensors may include, for example, pH, electrical conductivity (EC), cation exchange capacity (CEC), organic matter (OM) content, etc. Water properties that can be measured in the regions using one or more sensors and / or extracted from image data of the crop field 204 for these regions may include, for example, water flow patterns, etc. Topographic properties that can be extracted for these regions based on the topographic maps of the crop field 204 and / or the field surveys, image data of the crop field 204, etc., may include, for example, elevation, slope, inclination, surface orientation, etc. The regional maps may be stored in one or more remote networked resources 208, which can be accessed and retrieved by the crop protection material calculator 220 via network 206.

[0130] The crop protection material calculator 220 can further calculate a ranking score for each of the multiple segments of the crop field 204 based on the distribution of pests identified in the corresponding segments. For example, the crop protection material calculator 220 can calculate the ranking score proportionally to the distribution of pests, such that a high distribution of pests can be converted into a high ranking score, and a low distribution of pests can be converted into a low ranking score. Therefore, segments identified as having a high distribution of pests may be assigned a high ranking score, while segments identified as having a low distribution of pests may be assigned a low ranking score.

[0131] According to some embodiments, crop field 204 can be plotted into multiple segments based on pest distribution identified by analysis of past sensory data (e.g., one or more images of crop field 204, one or more spectral maps of crop field 204). Past sensory data (especially past sensory data captured during one or more previous growth cycles in crop field 204) can be analyzed to identify pest scarcity of one or more pests in crop field 204.

[0132] Now for reference Figure 3A and Figure 3B This is a schematic diagram of an exemplary crop field, based on the distribution of harmful organisms identified in each segment according to some embodiments of the present invention, drawn as multiple segments for applying crop protection materials at variable rates. Exemplary crop field 204A (e.g., Figure 3A The crop field 204 shown can be planted with one or more crops.

[0133] A crop protection material calculator (such as crop protection material calculator 220) can analyze one or more images of crop field 204A to identify visual evidence and / or indications of the presence of one or more pests (e.g., weeds, nematodes, mites, fungi, insects, pathogens, etc.) that indicate the presence of one or more of the (one or more) pests that are injurious to the (one or more) crops planted in crop field 204A, and / or visual evidence and / or indications of the presence of a pest (e.g., a weed) that inhibits and / or slows plant growth.

[0134] Based on this analysis, crop protection material calculator 220 can map crop field 204A into a plurality of sections 302 as shown in Figure 3B . In particular, crop protection material calculator 220 can divide crop field 204A into sections 302 based on the distribution of pests identified in each section 302.

[0135] In addition, crop protection material calculator 220 can calculate a ranking score for each of the plurality of sections 302, which can be directly proportional to the distribution of pests identified in the respective section. For example, crop protection material calculator 220 can set a pest distribution scale with a plurality of graduated values, such as 1-5, where a value of 5 indicates a very high distribution of pests (presence, volume, density, concentration, etc.), and a value of 1 can indicate a very low density of pests, and possibly the absence of pests.

[0136] Referring again to Figure 1 .

[0137] As shown at 108, crop protection material calculator 220 can calculate, for each of the plurality of sections of crop field 204, a respective dose of one or more selected crop protection materials based on the distribution of the (one or more) pests identified in the respective section. In particular, crop protection material calculator 220 can calculate a respective dose that is estimated to be effective to control (e.g., eradicate, kill, incapacitate, repel, deter, suppress, limit, and / or otherwise impede) the (one or more) pests in the respective section as reflected by the distribution of pests identified in the respective section.

[0138] The crop protection material calculator 220 can apply one or more criteria to estimate effective control of the pest(s) in each segment of the crop field 204. For example, effective control can reflect that a predefined minimum estimated percentage of the pest(s) in the respective segment is estimated to be eradicated and / or driven off, e.g., 70%, 80%, 90%, 95%, etc. In another example, effective control can reflect that the pest(s) are estimated to have less than a predefined maximum percentage impact on reducing crop yield in the respective segment, e.g., 30%, 20%, 10%, 5%, etc. However, the crop protection material calculator 220 can apply additional considerations to calculate respective dosages for one or more segments that are estimated to have desired effectiveness. For example, in some cases, even with a significantly high dosage of the crop protection material(s), good control can not be achieved, e.g., with more than a certain percentage of the pests eradicated, e.g., reaching 50% in one or more segments. However, it can still be desirable to apply the crop protection material(s) in these segments, possibly at a high dosage, to limit and ideally prevent the pest(s) from further expanding in the segment(s) and / or spreading to other segment(s) of the crop field 204.

[0139] Accordingly, the crop protection material calculator 220 can calculate increased dosages for segments that are identified to have higher pest distribution, while it can calculate reduced dosages for segments that are identified to have lower pest distribution. For example, Figure 3B Some of the segments 302 are identified to have Figure 3B high pest distribution, reflected in high values (e.g., 4-5) in the pest distribution map 300, other segments 302 are identified to have Figure 3B moderate pest distribution, reflected in moderate values (e.g., 2-3) in the pest distribution map 300, and some other segments 302 are identified to have Figure 3B little pest distribution, reflected in low values (e.g., 1) in the pest distribution map 300, and possibly no pest distribution. In this case, the crop protection material calculator 220 can calculate increased dosages for segments labeled with values 4-5, reduced dosages for segments labeled with values 2-3, and small dosages for segments labeled with values 1.

[0140] Optionally, the crop protection material calculator 220 can employ one or more ML models (e.g., neural networks, SVMs, etc.) to calculate effective dosages of crop protection material(s) for one or more segments using AI. The ML models can be trained and learned to establish correlations between application parameters of crop protection materials (e.g., type, dosage, application time, etc.) and their effects on pests (i.e., their effectiveness in controlling pests (e.g., eradication and / or repelling percentages, effects on yield percentages, etc.)). The ML models can be trained and learned to optionally establish correlations between application parameters of crop protection materials (e.g., type, dosage, application time, etc.) and their effects on pests (i.e., their effectiveness in controlling pests (e.g., eradication and / or repelling percentages, effects on yield percentages, etc.)) for various crop field topologies and / or different residual effects parameters and / or combinations thereof. Thus, the ML model(s) can be trained in one or more supervised and / or unsupervised training sessions using one or more training datasets that include information related to effects of different dosages of different crop protection materials applied to various crop fields infected with one or more pests on the pests and / or crop yields. The ML model(s) can thus learn, adjust, and evolve to establish correlations between selected crop protection materials and / or dosages and effective control of pests. Thus, the crop protection material calculator 220 can apply the trained ML model(s) to the pest distribution levels identified in one or more segments, e.g., to the image(s) delineating the segment(s) to calculate respective dosages estimated to be effective in eradicating the pest(s) identified in the respective segment(s).

[0141] According to some embodiments, the crop protection material calculator 220 can calculate respective dosages of multiple crop protection materials for one or more sections in the crop field 204. For example, if the crop protection material calculator 220 identifies that the crop in one or more sections is infected with multiple different harmful organisms, such as a certain type of weed and an insect. In this case, the crop protection material calculator 220 can calculate respective dosages of multiple crop protection materials that are estimated to be effective in eradicating the weed and the certain insect. In another example, the crop protection material calculator 220 can estimate a combination of multiple crop protection materials that are to be applied in one or more sections that are effective in eradicating a particular harmful organism identified in the respective section(s). In particular, the crop protection material calculator 220 can estimate that the combination of multiple crop protection materials can be more effective in eradicating the particular harmful organism and / or reducing the residue of the infection of the crop product(s) compared to a single crop protection material. For example, assume that a certain type of weed is identified in one or more sections of the crop field 204. The crop protection material calculator 220 can estimate that a combination of two herbicides can be more effective in eradicating the certain weed compared to any single herbicide.

[0142] Optionally, one or more of the crop protection material(s) selected for application in the crop field 204 is selected according to the type of the harmful organism(s) identified in the crop field based on an analysis of the sensory data (e.g., images, spectra, maps, etc.) generated for the crop field 204, the report generated for the crop field 204, and / or a combination thereof.

[0143] As shown in 110, the crop protection material calculator 220 can calculate a variable rate application of at least a portion of the total dosage of the crop protection material(s) in the crop field 204. The crop protection material calculator 220 can calculate the variable rate application to apply the respective dosages calculated for at least some sections in the crop field 204.

[0144] If the cumulative dosage of the dosages of all sections of the crop field 204 (i.e., the sum of all dosages of all sections) is less than or equal to the total dosage allowed for the entire crop field 204, the crop protection material calculator 220 can calculate a variable rate application to be applied to all sections.

[0145] However, if the cumulative dosage exceeds the total dosage, the crop protection material calculator 220 can calculate a variable rate application of the crop protection material(s) to be applied only in a subset of sections of the crop field 204. In particular, the crop protection material calculator 220 can select one or more sections for the subset that add up to a cumulative dosage that does not exceed the total dosage.

[0146] The crop protection material calculator 220 can apply one or more selection schemes and / or criteria to select the segments in the subset in which to apply the crop protection material according to the variable rate application. For example, the crop protection material calculator 220 can select the subset to include one or more highest ranked segments of the plurality of segments having the highest ranking scores. In particular, the crop protection material calculator 220 can select the subset of the highest ranked segments having cumulative dosages that do not exceed the total dosage. This can be used to eradicate the pest(s) in the segments most heavily infected by the pest(s) while other segments having lower levels of infection and thus expected to survive the pest damage can not be treated. In another example, the crop protection material calculator 220 can select the subset to include the plurality of segments according to the geographic location of the segments in the crop field 204. For example, the crop protection material calculator 220 can select the subset to include the westernmost segments of the crop field 204 while excluding at least some segments east of the crop field 204 from the subset. This can be effective in the presence of limited applicator system(s) 202 that can have limited travel and / or coverage ranges and thus can not be able to cover the entire crop field to apply the crop protection material(s). In another example, the crop protection material calculator 220 can select the subset to include the plurality of segments to limit the spread and / or extension of the pest(s) from one or more selected segments to one or more other segments.

[0147] Optionally, the crop protection material calculator 220 calculates the variable rate application to avoid applying the selected crop protection material(s) in one or more segments of the crop field 204 such that the segment(s) are not treated. The crop protection material calculator 220 can calculate the variable rate application to not treat such segment(s), for example, to avoid exceeding the total dosage allowed to be applied in the crop field 204 at the cost of the yield of the crop potentially being reduced due to the pest(s) in the untreated segment(s) not being controlled. In another example, the crop protection material calculator 220 can calculate the variable rate application to avoid treating one or more segments if the crop protection material calculator 220 estimates that the selected crop protection material(s) can not be effective in controlling the pest(s) identified in the segment(s) and that applying one or more different crop protection materials in the segment(s) can be more effective.

[0148] Further, if the crop protection material calculator 220 calculates a respective dosage for each of a plurality of different crop protection materials for one or more segments of the crop field 204, the crop protection material calculator 220 can further calculate a respective variable rate application for each of the plurality of crop protection materials.

[0149] As shown at 112, the crop protection material calculator 220 can output, via the I / O interface 210, one or more plans and / or prescriptions comprising instructions for applying the crop protection material(s) in the crop field 204 according to the computed variable rate application.

[0150] The application instructions can be used by one or more applicator systems 202 configured to apply the crop protection material(s) in the crop field 204 such that the rate of the sprayed crop protection material(s) is adjusted in real-time in real-time according to the variable rate application as defined by these instructions.

[0151] In case a plurality of crop protection materials is applied in at least some segments of the crop field 204 according to respective plural variable rate applications, respectively, a plurality of applicator systems 202 each configured to apply a specific one of the crop protection materials can operate to apply a certain one of the crop protection materials in one or more segments. For example, one or more first applicator systems 202 can be used to apply a first crop protection material according to a first variable rate application, and one or more second applicator systems 202 can be used to apply a second crop protection material according to a second variable rate application.

[0152] According to some embodiments, the crop protection material calculator 220 can apply an alternative sequence to compute the variable rate application. In such an alternative workflow, the crop protection material calculator 220 can first compute an effective dose for each segment of the crop field 204 according to the pest distribution identified in the respective segment, as described in step 108. The crop protection material calculator 220 can then compute a variable rate application for applying the crop protection material(s) in the segments of the crop field 204 according to the respective effective dose computed for each segment, as described in step 110. The plan generated by the crop protection material calculator 220 comprising instructions for the variable rate application as described in step 112 can be approved if the cumulative dose of all effective doses does not exceed the total dose computed for the crop field 204, and optionally rejected if the cumulative dose exceeds the total dose. Optionally, if the cumulative dose exceeds the total dose, the crop protection material calculator 220 can adjust the instructions to instruct to apply the crop protection material(s) according to the variable rate application only in a subset of the plural segments. The crop protection material calculator 220 can select the subset according to one or more selection schemes and / or criteria as described before, e.g., according to the ranking score computed for the segments, according to the geographical location of the segments, according to the ability to limit the spread and / or extension of the pest(s) from the selected segments to other segments, etc.

[0153] Additionally and / or alternatively, one or more multiple-application applicator systems 202 can be used to apply multiple crop protection materials in parallel and / or serially according to respective variable rate applications. For example, a helicopter, such as helicopter 202B, can be configured to carry two separate containers, each containing a different crop protection material. Helicopter 202B can be operated to apply the two different crop protection materials in one or more sections of crop field 204 according to two respective variable rate applications. To this end, helicopter 202B can be flown over a respective section twice, such that on the first pass, helicopter 202B can be operated to apply a first crop protection material according to a first variable rate application instruction, and on the second pass, helicopter 202B can be operated to apply a second crop protection material according to a second variable rate application instruction. In the case where helicopter 202B is configurable and capable of applying both crop protection materials simultaneously, helicopter 202B can be operated to apply both crop protection materials simultaneously according to their respective variable rate application instructions.

[0154] The description of various embodiments of the application is presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others skilled in the art to understand the embodiments disclosed herein.

[0155] It is expected that during the life of a patent maturing from this application many relevant systems, methods and computer programs will be developed and the scope of the terms "sensor" and "crop protection material" is intended to include all such new technologies a priori.

[0156] As used herein, the term "about" means ±10%.

[0157] The terms "comprises", "comprising", "includes", "including", "having" and their conjugates mean "including but not limited to". This term encompasses the terms "consisting of" and "consisting essentially of".

[0158] The phrase "consisting essentially of" means that the composition or method can include additional ingredients and / or steps, but only if the additional ingredients and / or steps do not materially alter the basic and novel characteristics of the claimed composition or method.

[0159] As used herein, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. For example, the term “a compound” or “at least one compound” can include a plurality of compounds, including mixtures thereof.

[0160] The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any implementation described as “exemplary” is not necessarily to be construed as preferred or advantageous over other implementations.

[0161] The word “optionally” is used herein to mean “in some embodiments, provided and in other embodiments not provided.” Any particular embodiment of the application can include a plurality of “optional” features, unless such features conflict.

[0162] Throughout this application, various embodiments of the application can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as limiting the scope of the application. Therefore, the description of a range should be considered to have specifically disclosed the subranges and individual numbers within that range and to have specifically excluded any integer within that range that is not listed, even though such a range can be explicitly listed. For example, a description of a range such as from 1 to 6 should be considered to have specifically disclosed the subranges 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, 3 to 6, and 4 to 6 just as if each of these subranges was individually listed. This same principle applies to ranges with a different broad limit as well. For example, a range of from 1.0 to 6.0 should be considered to have specifically disclosed the subranges 1.0 to 3.0, 1.0 to 4.0, 1.0 to 5.0, 1.0 to 6.0, 2.0 to 4.0, 2.0 to 6.0, 3.0 to 6.0, and 4.0 to 6.0 just as if each of these subranges was individually listed.

[0163] Whenever a numerical range is indicated, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases “ranging / ranges between” a first indicate number and a second indicate number and “ranging / ranges from” a first indicate number “to” a second indicate number are used herein interchangeably and are meant to include the first and second indicate numbers and all the fractional and integral values therebetween.

[0164] The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any implementation described as “exemplary” is not necessarily to be construed as preferred or advantageous over other implementations.

[0165] The word “optionally” is used herein to mean “in some embodiments, provided and in other embodiments not provided.” Any particular embodiment of the application can include a plurality of “optional” features, unless such features conflict.

[0166] It should be understood that, for clarity, certain features of the invention described in individual embodiments may also be provided in combination in a single embodiment. Conversely, for simplicity, various features of the invention described in individual embodiments may also be provided individually or in any suitable sub-combination or, where appropriate, in any other described embodiment of the invention. Certain features described in various embodiments are not considered essential features of those embodiments unless the embodiment would be invalid without those elements.

[0167] Although the invention has been described in conjunction with specific embodiments thereof, it will be apparent to those skilled in the art that many alternatives, modifications, and variations will be readily apparent. Therefore, it is intended to cover all such alternatives, modifications, and variations falling within the spirit and broad scope of the appended claims.

[0168] All publications, patents, and patent applications mentioned in this specification are incorporated herein by reference in their entirety, as if each individual publication, patent, or patent application were specifically and individually designated as incorporated herein by reference. Furthermore, any reference or designation of any reference in this application should not be construed as an admission that such reference is prior art to the invention. The use of section headings should not be construed as necessarily limiting. Additionally, any priority documents of this application are incorporated herein by reference in their entirety.

Claims

1. A computer-implemented method for generating instructions for the variable-rate application of crop protection materials, the method comprising: Calculate the total dosage of at least one crop protection material that is permitted to be applied in a crop field, such that the residue of the at least one crop protection material in the crop product grown in the crop field does not exceed a predefined maximum residue limit (MRL). The total dosage is adjusted based on at least some of the multiple residual impact parameters of the crop field; The crop field is divided into multiple sections based on the distribution of at least one harmful organism in each of the multiple sections; The corresponding dosage of the at least one crop protection material that is estimated to be able to effectively control the at least one pest in each of the plurality of segments is calculated based on the distribution of pests in the corresponding segments. Calculate the cumulative dose of the corresponding doses in the multiple segments; When the cumulative dose of the corresponding doses in the multiple segments exceeds the total dose: Calculate the ranking score for each of the multiple segments based on the distribution of the corresponding pests in the corresponding segments; Based on the ranking score, at least one subset of the segments is selected from the plurality of segments, such that the subset includes the plurality of highest-ranking segments among the plurality of segments that have a cumulative dose not exceeding the total dose; The total dose of the crop protection material is calculated based on the estimated dose for each of the plurality of segments, and applied at a variable rate in the crop field. as well as Output instructions for applying the at least one crop protection material in the crop field at the variable rate, wherein the instructions further define the application of the at least one crop protection material in at least one subset of the plurality of sections at the variable rate; The plurality of residual impact parameters include: the type of the at least one crop protection material, the growth stage of the crop, the estimated biomass of the crop, the estimated residues from at least one previous application of a crop protection material in the crop field, the estimated residual crop protection material for at least one planned future application of a crop protection material for the crop field, the organic matter (OM) content in the crop field, the type of the at least one pest, the type of the at least one crop protection material previously applied in the crop field, and the environmental conditions in the geographical area of ​​the crop field.

2. The method as described in claim 1, wherein, The instructions further define that, when multiple crop protection materials are selected for application in at least one section, the multiple crop protection materials shall be applied according to their respective variable application rates.

3. The method of claim 1, further comprising selecting the at least one crop protection material based on at least one pest identified based on the distribution of the pest.

4. The method of claim 1, wherein, The at least one harmful organism is a member of the group consisting of weeds, nematodes, mites, fungi, insects, and disease pathogens.

5. The method of claim 1, wherein, The at least one crop protection material is a member of the group consisting of: herbicides, fungicides, pest control agents, nematicides, insecticides, acaricides, surfactants, and adjuvants.

6. The method of claim 1, wherein, The distribution of the pests is identified based on the analysis of at least one image of the crop field.

7. The method of claim 1, wherein, The distribution of the pests is identified based on the analysis of at least one past image of the crop field captured in at least one previous growth cycle.

8. The method of claim 1, wherein, The distribution of the pests is identified based on the analysis of at least one crop growth report generated for the crop field.

9. The method of claim 1, wherein, The distribution of the pests is identified based on the analysis of sensory data captured in the crop field by at least one sensor.

10. The method of claim 1, wherein, The drawing of the multiple segments is further based on a regional map of the crop field. The regional map divides the crop field into multiple regions based on at least one of multiple soil attributes of each region, including soil attributes, water attributes, and topographic attributes.

11. The method of claim 1, wherein, The effective control reflects at least a predefined minimum percentage of eradication and / or removal of the at least one pest in the corresponding section.

12. The method of claim 1, wherein, The effective control reflects limiting the impact of the at least one pest in the corresponding section to a predefined maximum percentage below the yield of the crop.

13. The method of claim 1, further comprising applying at least one machine learning model to calculate a corresponding dose of at least one of the plurality of segments, the at least one machine learning model being trained to establish a correlation between the plurality of doses of the at least one crop protection material and the effective control of the plurality of pest distributions of the at least one pest.

14. The method of claim 1, further comprising first calculating the variable-rate administration, and then calculating the total dose in the following manner: The crop field is divided into the multiple sections based on the distribution of the harmful organisms; The appropriate dosage of the at least one crop protection material for each of the plurality of segments is calculated based on the distribution of harmful organisms in the corresponding segments; The variable rate of administration is calculated based on the dose estimated for each of the plurality of segments; as well as The total dosage is calculated such that the residue of at least one crop protection material in the crop product grown in the crop field does not exceed a predefined MRL.

15. A system for generating instructions for the variable-rate application of crop protection materials, the system comprising: At least one processor that executes code, the code comprising instructions that, when executed by the at least one processor, cause the at least one processor to perform the method according to any one of claims 1 to 14.

16. A computer program product comprising computer-readable program code executable by at least one processor when retrieved from a non-transitory computer-readable medium, the program code including code instructions that, when executed by the at least one processor, cause the at least one processor to perform the method according to any one of claims 1 to 14.

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