Method for improving crop rotation

Abstract

Computationally implemented methods, computing systems and computer program products disclosed herein relate to the calculation of risk values for crop plant phytotoxicity based on the classification of digital images into vegetation classes, including additional agronomic data and the provision of agricultural recommendations based on these risk values.

Description

[0001] BCS246146 FC-Text / / EK-JK 2025-12-17

[0002] Method for improving crop rotation

[0003] COPYRIGHT NOTICE

[0004] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in a Patent Office patent file or records, but otherwise reserves all copyright or rights whatsoever. © 2023 Bayer AG

[0005] FIELD OF THE DISCLOSURE

[0006] Computationally implemented methods, computing systems and computer program products disclosed herein relate to the calculation of risk values for crop plant phytotoxicity based on the classification of digital images into vegetation classes, including additional agronomic data and the provision of agricultural recommendations based on these risk values.

[0007] BACKGROUND

[0008] Herbicide applications of crop protection product may be limited due to variety of biotic and abiotic factors that influence efficacy, phytotoxicity, and persistence among other factors of those crop protection products.

[0009] As crop protection products are regulated by governmental authorities in countries regarding efficacy, environmental safety and other characteristics, the respective labels issued by those authorities for crop protection products like herbicide comprise exceptions for thresholds for application patterns eg in terms of timing, intervals and dosage depending on environmental factors including pH, soil organic matter, weather conditions like precipitation.

[0010] In particular in crop rotation, so the practice of growing different crop species in the same area over a number of growing seasons, application schemes of crop protection products and their persistence in the soil have to be considered when selecting the crops for a certain crop rotation scheme aside from other factors like yield, nutrient requirement etc.

[0011] US2022 / 0270250 Al describes a method to assess phytotoxicity allowing an assessment of phytotoxicity such as chlorosis, necrosis, stunting and bleaching of single plants or small planted areas the analysis of digital images. However this reference is not allowing to assess the ground cover which is not related to phytotoxicity as this is an assessment of a mix of live plants and dead or dormant vegetation eg stubble. Neither does this reference provide further steps how to calculate based on the ground cover the risk for phytoptoxicity due to residual crop protection product which could harm certain sensitive crops over a certain period of time.

[0012] Carryover of crop protection product can be influenced by many factors as described above but is also depending on soil conditions at the time of application, in particular the amount and type of living and non-living plant matter on or in the soil or the amount of bare soil exposed to the crop protection product applied. This is due to the fact that living and dead vegetation may have an impact on crop protection product interception and adsorption. In addition, vegetation whether dead or alive will retain moisture in the ground cover which supports growth of microorganism potentially capable of metabolizing and thereby degrading crop protection products. Dead vegetation will intercept and potentially bind the crop protection product, thereby making it unavailable for uptake; while living vegetation will intercept and metabolize the crop protection product making it also unavailable for uptake to the crop planted thereafter. This is an important factor influencing the amount of soil residual crop protection product and this will be specific to any agricultural location at any given time point. Additional factors influencing the amount of soil residual crop protection product are agronomical data including the type of agronomic methods applied on that location eg no-till and tilling practices, weather data or soil properties. Also different crop species show different sensitivities towards certain crop protection BCS246146 FC-Text / / EK-JK 2025-12-17 product classes. For example the active ingredient Pyrasulfotole , a herbicide applied in cereals for the control of broadleaf (dicot) weed species such as Kochia is known to cause crop injury in lentil which is a dicot crop species grown in rotation with cereals. Therefore, there is a need to provide methods assessing the risk of crop injury or phytotoxicity in a time and location specific manner based on the assessment of different agronomic data such as agronomic practices, ground cover, soil properties and provide recommendation for future agronomic activities such as planting of certain crops in crop rotation or application of crop protection products. Those methods will be even more beneficial if they can be done in real time on an agricultural location with hand held devices preferably directly by growers or agronomists.

[0013] SUMMARY

[0014] These problems are solved by the subject matter of the independent claims of the present disclosure. Preferred embodiments are defined in the dependent claims, the description and the drawings. The objects of the present invention include a method, a system and a computer program product for providing agronomic recommendations based on the calculating fractions for vegetations classes based on the analysis of digital images and additional agronomic data.

[0015] In a first aspect, the present disclosure relates to a computationally implemented method comprising Receiving one or more digital images of one or more locations of an agricultural area;

[0016] Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images; Receiving additional agronomic data ;

[0017] Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;

[0018] Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

[0019] In another aspect, the present disclosure provides a computing system comprising: a processor; and a memory storing an application program configured to perform, when executed by the processor, an operation, the operation comprising:

[0020] Receiving the one or more digital images of one or more locations of an agricultural area;

[0021] Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images; Receiving additional agronomic data ;

[0022] Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;

[0023] Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

[0024] In one embodiment the agronomic data comprise application parameters of one or more crop protection product, soil data, weather data.

[0025] In one embodiment in the disclosed method the vegetation classes are comprised of the following classes: living vegetation (crop / weed / canopy), dead vegetation (crop / weed / residue) and no vegetation (soil).

[0026] In one embodiment in the method a further step comprising generating a script for planting the subsequent crop is disclosed.

[0027] In one embodiment in the method a further step comprising generating a script for the application of one or more crop protection product to that agricultural location is disclosed.

[0028] In one embodiment in the method the agricultural field has been subjected to no -till farming in the current or previous cropping cycle. BCS246146 FC-Text / / EK-JK 2025-12-17

[0029] In one embodiment in the method the agricultural field has been treated with soil residual crop protection products.

[0030] In another aspect, the present disclosure provides a computer program product comprising instructions which, when the program is executed by a computing system, cause the computing system to carry out the following steps:

[0031] Receiving the one or more digital images of one or more locations of an agricultural area;

[0032] Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images;

[0033] Receiving additional agronomic data ;

[0034] Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;

[0035] Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

[0036] In one embodiment the computer program product comprises an additional step the agronomic recommendation comprises planting a subsequent crop or applying a crop protection product.

[0037] A computer program product according to claim 9 or 10, in which the agronomic data comprises application parameters of one or more crop protection product, soil data, weather data.

[0038] In one embodiment the vegetation classes are comprised of the following classes: living vegetation (canopy), dead vegetation (residue) and no vegetation (soil).

[0039] In one embodiment the computer program product comprises a step for generating a script for planting the subsequent crop.

[0040] In one embodiment the computer program product comprises a step for generating a script for the application of one or more crop protection product to that agricultural location.

[0041] In one embodiment in the computer program product the agricultural field has been subjected to no-till farming in the current or previous cropping cycle.

[0042] In one embodiment in the computer program product the agricultural field has been treated with soil residual crop protection products.

[0043] In one embodiment a kit comprising a computer program product according to any of claims 9 to 16, or a computationally implemented method according to any of claims 1 to 8 and a device or app is described.

[0044] BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Some implementations of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all implementations of the disclosure are shown. Indeed, various implementations of the disclosure may be embodied in many different forms and should not be construed as limited to the implementations set forth herein; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0046] Fig. 1 is a block diagram of a computing system or a computer program product that can be used in the various embodiments of the invention described.

[0047] Fig. 2 shows schematically an embodiment of the computer-implemented method of the present disclosure in form of a flow chart.

[0048] Fig. 3 shows a schematic drawing of the design of field trials assessing the impact of different agronomic factors and applied crop protection products.

[0049] Fig. 4 shows an example of the user interface of a mobile app providing an agronomic recommendation. BCS246146 FC-Text / / EK-JK 2025-12-17

[0050] DETAILED DESCRIPTION

[0051] The invention will be more particularly described below without distinguishing between the aspects of the invention (method, computing system, a computer program product). On the contrary, the following description are intended to apply analogously to all the aspects of the invention, irrespective of in which context (method, computing system, a computer program product) they occur.

[0052] If steps are stated in an order in the present description or in the claims, this does not necessarily mean that the invention is restricted to the stated order. On the contrary, it is conceivable that the steps can also be executed in a different order or else in parallel to one another, unless one step builds upon another step, this absolutely requiring that the building step be executed subsequently (this being, however, clear in the individual case). The stated orders are thus preferred embodiments of the present disclosure.

[0053] As used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more” and “at least one.” As used in the specification and the claims, the singular form of “a”, “an”, and “the” include plural referents, unless the context clearly dictates otherwise. Where only one item is intended, the term “one” or similar language is used. Also, as used herein, the terms “has”, “have”, “having”, or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based at least partially on” unless explicitly stated otherwise. Further, the phrase “based on” may mean “in response to” and be indicative of a condition for automatically triggering a specified operation of an electronic device (e.g., a controller, a processor, a computing device, etc.) as appropriately referred to herein.

[0054] Some implementations of the present disclosure will be described more fully with reference to the accompanying drawings, in which some, but not all implementations of the disclosure are shown. Indeed, various implementations of the disclosure may be embodied in many different forms and should not be construed as limited to the implementations set forth herein; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0055] Fig. 1 shows schematically an embodiment of the computationally implemented method of the present disclosure in form of a flow chart.

[0056] Receiving the one or more digital images of one or more locations of an agricultural area;

[0057] Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images;

[0058] Receiving additional agronomic data ;

[0059] Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;

[0060] Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

[0061] The method (100) comprises the steps:

[0062] (110) Receiving the one or more digital images of one or more locations of an agricultural area;

[0063] (120) Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images;

[0064] (130) Receiving additional agronomic data ;

[0065] (140) Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area; (150) Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

[0066] The operations in accordance with the teachings herein may be performed by at least one computer program product specially constructed for the desired purposes or general -purpose computing system BCS246146 FC-Text / / EK-JK 2025-12-17 specially configured for the desired purpose by at least one computer program stored in a typically non- transitory computer readable storage medium.

[0067] The operations in accordance with the teachings herein may be performed by at least one computing system specially constructed for the desired purposes or general-purpose computing system specially configured for the desired purpose by at least one computer program stored in a typically non -transitory computer readable storage medium.

[0068] A “computing system” is a system for electronic data processing that processes data by means of programmable calculation rules. Such a system usually comprises a “computer”, that unit which comprises a processor for carrying out logical operations, and also peripherals.

[0069] In computer technology, “peripherals” refer to all devices which are connected to the computer and serve for the control of the computer and / or as input and output devices. Examples thereof are monitor (screen), printer, scanner, mouse, keyboard, drives, camera, microphone, loudspeaker, etc. Internal ports and expansion cards are, too, considered to be peripherals in computer technology.

[0070] Computing systems of today are frequently divided into desktop PCs, portable PCs, laptops, notebooks, netbooks and tablet PCs and so-called handhelds (e.g. smartphone); Computing systems also include cloud-hosted systems where one or more steps of the computer-implemented method are performed remotely over the internet. Computing systems also include web server, database server, application servers or cluster computing. All these systems can be utilized for carrying out the invention.

[0071] The term “non-transitory” is used herein to exclude transitory, propagating signals or waves, but to otherwise include any volatile or non-volatile computer memory technology suitable to the application. The term “computationally implemented” should be broadly construed to cover a method in which one or more computing device or one or more computing systems including networks are used to implement at least one step of the method.

[0072] The term “computing device” should be broadly construed to cover any kind of electronic device with data processing capabilities, including, by way of non-limiting example, personal computers, servers, embedded cores, computing system, communication devices, processors (e.g., digital signal processor (DSP)), microcontrollers, field programmable gate array (FPGA), application specific integrated circuit (ASIC), etc.) and other electronic computing devices.

[0073] The term “computer program product” means a non-transitory computing device -readable medium having computing device -readable code embodied therein, the computing device -readable code configured such that, when executed by a suitable computing device or processor, causes the computing device or processor to perform the methods disclosed herein In the context of such non-transitory computing device readable media, for the purpose of executing computing device readable code, when the computing device or processor is caused to perform the steps of obtaining information or data, this means retrieving the corresponding information of the data from the data storage device. Computing device executable instructions corresponding to each of the processing steps of at least one of the methods set forth herein. The instructions may be subdivided into subroutines and / or stored in one or more files that may be linked statically or dynamically. Another embodiment involving a computer program product comprises computing device -executable instructions corresponding to each element of at least one of the computing device, systems and / or products set forth herein. The instructions may be subdivided into subroutines and / or stored in one or more files that may be linked statically or dynamically.

[0074] The term “process” as used above is intended to include any type of computation or manipulation or transformation of data represented as physical, e.g., electronic, phenomena which may occur or reside e.g., within registers and / or memories of at least one computer or processor. The term processor includes a single processing unit or a plurality of distributed or remote such units. BCS246146 FC-Text / / EK-JK 2025-12-17

[0075] Fig. 1 illustrates a computing system (1) according to some example implementations of the present disclosure in more detail.

[0076] Generally, a computing system of exemplary implementations of the present disclosure may be referred to as a computer and may comprise, include, or be embodied in one or more fixed or portable electronic devices. The computer may include one or more of each of a number of components such as, for example, a processing unit (20) connected to a memory (50) (e.g., storage device).

[0077] The processing unit (20) may be composed of one or more processors alone or in combination with one or more memories. The processing unit (20) is generally any piece of computer hardware that is capable of processing information such as, for example, data, computer programs and / or other suitable electronic information. The processing unit (20) is composed of a collection of electronic circuits some of which may be packaged as an integrated circuit or multiple interconnected integrated circuits (an integrated circuit at times more commonly referred to as a “chip”). The processing unit (20) may be configured to execute computer programs, which may be stored onboard the processing unit (20) or otherwise stored in the memory (50) of the same or another computer.

[0078] The processing unit (20) may be a number of processors, a multi -core processor or some other type of processor, depending on the particular implementation. For example, it may be a central processing unit (CPU), a field programmable gate array (FPGA), a graphics processing unit (GPU) and / or a tensor processing unit (TPU). Further, the processing unit (20) may be implemented using a number of heterogeneous processor systems in which a main processor is present with one or more secondary processors on a single chip. As another illustrative example, the processing unit (20) may be a symmetric multi-processor system containing multiple processors of the same type. In yet another example, the processing unit (20) may be embodied as or otherwise include one or more ASICs, FPGAs or the like. Thus, although the processing unit (20) may be capable of executing a computer program to perform one or more functions, the processing unit (20) of various examples may be capable of performing one or more functions without the aid of a computer program. In either instance, the processing unit (20) may be appropriately programmed to perform functions or operations according to example implementations of the present disclosure.

[0079] The memory (50) is generally any piece of computer hardware that is capable of storing information such as, for example, data, computer programs (e.g., computer-readable program code (60)) and / or other suitable information either on a temporary basis and / or a permanent basis . The memory (50) may include volatile and / or non-volatile memory, and may be fixed or removable. Examples of suitable memory include random access memory (RAM), read-only memory (ROM), a hard drive, a flash memory, a thumb drive, a removable computer diskette, an optical disk, a magnetic tape or some combination of the above. Optical disks may include compact disk - read only memory (CD-ROM), compact disk - read / write (CD-R / W), DVD, Blu-ray disk or the like. In various instances, the memory may be referred to as a computer-readable storage medium or data memory. The computer-readable storage medium is a non-transitory device capable of storing information, and is distinguishable from computer-readable transmission media such as electronic transitory signals capable of carrying information from one location to another. Computer-readable medium as described herein may generally refer to a computer- readable storage medium or computer-readable transmission medium.

[0080] In addition to the memory (50), the processing unit (20) may also be connected to one or more interfaces for displaying, transmitting and / or receiving information. The interfaces may include one or more communications interfaces and / or one or more user interfaces. The communications interface(s) may be configured to transmit and / or receive information, such as to and / or from other computer(s), network(s), database(s) or the like. The communications interface may be configured to transmit and / or receive information by physical (wired) and / or wireless communications links. The communications interface(s) may include interface(s) (41) to connect to a network, such as using technologies such as cellular telephone, Wi-Fi, satellite, cable, digital subscriber line (DSL), fiber optics and the like. In some examples, the communications interface(s) may include one or more short-range communications BCS246146 FC-Text / / EK-JK 2025-12-17 interfaces (42) configured to connect devices using short-range communications technologies such as NFC, RFID, Bluetooth, Bluetooth LE, ZigBee, infrared (e.g., IrDA) or the like.

[0081] The user interfaces may include a display (30). The display (screen) may be configured to present or otherwise display information to a user, suitable examples of which include a liquid crystal display (LCD), light-emitting diode display (LED), plasma display panel (PDP) or the like. The user input interface(s) (11) may be wired or wireless, and may be configured to receive information from a user into the computing system (1), such as for processing, storage and / or display. Suitable examples of user input interfaces include a microphone, image or video capture device, keyboard or keypad, joystick, touch-sensitive surface (separate from or integrated into a touchscreen) or the like. In some examples, the user interfaces may include automatic identification and data capture (AIDC) technology (12) for machine -readable information. This may include barcode, radio frequency identification (RFID), magnetic stripes, optical character recognition (OCR), integrated circuit card (ICC), and the like. The user interfaces may further include one or more interfaces for communicating with peripherals such as printers and the like.

[0082] As indicated above, program code instructions (60) may be stored in memory (50), and executed by processing unit (20) that is thereby programmed, to implement functions of the systems, subsystems, tools and their respective elements described herein. As will be appreciated, any suitable program code instructions (60) may be loaded onto a computer or other programmable apparatus from a computer- readable storage medium to produce a particular machine, such that the particular machine becomes a means for implementing the functions specified herein. These program code instructions (60) may also be stored in a computer-readable storage medium that can direct a computer, processing unit or other programmable apparatus to function in a particular manner to thereby generate a particular machine or particular article of manufacture. The instructions stored in the computer-readable storage medium may produce an article of manufacture, where the article of manufacture becomes a means for implementing functions described herein. The program code instructions (60) may be retrieved from a computer- readable storage medium and loaded into a computer, processing unit or other programmable apparatus to configure the computer, processing unit or other programmable apparatus to execute operations to be performed on or by the computer, processing unit or other programmable apparatus.

[0083] Retrieval, loading and execution of the program code instructions (60) may be performed sequentially such that one instruction is retrieved, loaded and executed at a time. In some example implementations, retrieval, loading and / or execution may be performed in parallel such that multiple instructions are retrieved, loaded, and / or executed together. Execution of the program code instructions (60) may produce a computer-implemented process such that the instructions executed by the computer, processing circuitry or other programmable apparatus provide operations for implementing functions described herein.

[0084] Execution of instructions by processing unit, or storage of instructions in a computer-readable storage medium, supports combinations of operations for performing the specified functions. In this manner, a computing system (1) may include processing unit (20) and a computer-readable storage medium or memory (50) coupled to the processing circuitry, where the processing circuitry is configured to execute computer-readable program code instructions (60) stored in the memory (50). It will also be understood that one or more functions, and combinations of functions, may be implemented by special purpose hardware -based computing systems and / or processing circuitry which perform the specified functions, or combinations of special purpose hardware and program code instructions.

[0085] The computing system of the present disclosure may be in the form of a laptop, notebook, netbook, and / or tablet PC; it may also be a component of an MRI scanner, a CT scanner, or an ultrasound diagnostic machine.

[0086] In another aspect, the present disclosure provides a computer program product. Such a computer program product comprises a non-volatile data carrier, such as a CD, a DVD, a USB stick or other medium for storing data. A computer program is stored on the data carrier. The computer program can BCS246146 FC-Text / / EK-JK 2025-12-17 be loaded into a working memory of a computing system (in particular, into a working memory of a computing system of the present disclosure), where it can cause the computing system to perform the following steps:

[0087] Receiving the one or more digital images of one or more locations of an agricultural area;

[0088] Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images; Receiving additional agronomic data ;

[0089] Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;

[0090] The computer program product may also be marketed in combination with a device or an app suitable for a portable device including a mobile or tablet.

[0091] Such a combination is also referred to as a kit. Such a kit includes the device or app and the computer program product. It is also possible that such a kit includes the device or app and means for allowing a purchaser to obtain the computer program, e.g., download it from an Internet site. These means may include a link, i.e., an address of the Internet site from which the computer program may be obtained, e.g., from which the computer program may be downloaded to a computing system connected to the Internet. Such means may include a code (e.g., an alphanumeric string or a QR code, or a DataMatrix code or a barcode or other optically and / or electronically readable code) by which the purchaser can access the computer program. Such a link and / or code may, for example, be printed on a package of the crop protection product and / or printed on a package of the seeds. A kit is thus a combination product comprising device or app and a computer program product or the computationally implemented method (e.g., in the form of access to the computer program product or in the form of executable program code on a data carrier) that is offered for sale together.

[0092] In the first step one or more digital images of one or more locations of an agricultural area are received.

[0093] Digital images are images suitable for computer implemented processing and analysis composed of discrete units that represent spatial information like the x , y or z coordinates and additional attributes like intensity, color. The two main types of digital images include raster images or vector images. The smallest unit within a digital image is a pixel representing a specific point in a image and containing information about color and brightness. Images types are black-and-white (binary), grey scale, color or multispectral comprising information on more than one spectral band including in the infrared, ultraviolet, visible, X-ray, acustic or radar field. In hyperspectral images each pixel comprise a broad range of information across the spectrum.

[0094] In LiDAR (Light detection and ranging) images are generated by using a laser for emitting rapid pulses of light, a scanner for directing the light pulses, a detector / sensor for receiving the reflected light pulses, a device to determine the precise positioning and orientation data thereby providing a point cloud which can be used to create a 3D model.

[0095] Digital images can be classified acquired from various sources, including satellite data, drone images, ground-based agricultural machinery equipped with imaging technology (so called “see-and-spray equipment), and images from user (such as a farmer). Different camera technologies are utilized for these applications. Satellite imagery provides a comprehensive view of large agricultural areas. Sensors onboard satellites capture multispectral or hyperspectral images, allowing for the analysis of vegetation health, crop plant conditions, and green canopy cover fraction. Satellite cameras utilize various technologies, including charge -coupled device (CCD) and complementary metal -oxide-semiconductor (CMOS) sensors, which are capable of capturing data across different wavelengths, such as visible, nearinfrared, and shortwave infrared. Drones, or unmanned aerial vehicles (UAVs), equipped with specialized cameras can be used for high-resolution imaging of agricultural fields. These images can provide detailed insights into canopy cover fraction at a finer spatial resolution compared to satellite data. Drone cameras often utilize CMOS or CCD sensors and may capture RGB (visible light), near- BCS246146 FC-Text / / EK-JK 2025-12-17 infrared, hyperspectral or multispectral imagery for precise analysis of canopy cover. Some agricultural machinery, such as tractor-mounted sensors or imaging systems, can capture ground-level images of fields during farming operations. These images can be used to assess the vegetation cover.

[0096] Alternatively, a camera from a mobile, tablet or other handheld computing devices can be used. The camera technology integrated into such systems may include images such as RGB, black or white or Griineberg scale or multispectral, hyperspectral or LiDAR to gather relevant data for analyzing living or dead vegetation fraction.

[0097] In one embodiment the one or more digital images are RGB images, LiDAR images, multispectral images or hyperspectral images.

[0098] In another embodiment the one or more digital images are acquired by using a mobile device. In one embodiment the mobile device is a smart phone, mobile phone, handheld or tablet. In one embodiment the one or more digital images are acquired using a Unmanned Aerial Vehicle (UAV), in particular a fixed wing drone, single rotor or multi-rotor drone.

[0099] In one embodiment the one or more digital image are acquired at the end of the growing season (in or after BBCH 90), before planting the crop plant (before BBCH 0).

[0100] In one embodiment the one or more digital image are acquired within the same BBCH stage, up to two BBCH stages before or two BBCH stages after the BBCH stage, in which the crop protection product is applied.

[0101] In one embodiment the one or more digital image are acquired within the same BBCH stage, in which the crop protection product is applied.

[0102] An agricultural area means a spatially delimitable region of the Earth's surface on which the plants grow. In one embodiment the agricultural area is at least partly utilized agriculturally in that crop plants are planted in one or more fields, are supplied with nutrients and are harvested. The area may also be or comprise a silviculturally utilized region of the Earth's surface (for example a forest). Gardens, parks or the like in which vegetation exists solely for human pleasure are covered by the term area.

[0103] An agricultural area may include a multitude of fields for crop plants. In one embodiment, an area corresponds to a growing area for a crop plant (for definition of a growing area see, for example, Journal fur Kulturpflanzen, 61 (7). p. 247-253, 2009, ISSN 0027-7479). In another embodiment, an area corresponds to a biome (for definition of equivalent German term Boden -Klima-Raum see, for example, Nachrichtenbl. Deut. Pflanzenschutzd., 59(7), p. 155-161, 2007, ISSN 0027-7479).

[0104] A location means a preferably contiguous region within an agricultural area. A location may be one or more fields in which a specific crop plant is being grown. The location is preferably being farmed by a person having registered access to a multitude of imaging devices and optionally one or more plant analysis devices.

[0105] In one embodiment the location is a field or a part of a field in which a grower or farmers grows a commercial crop plant. In another embodiment the location is a field in which experimental or demonstration trials have been planted.

[0106] Crop plant means a plant or plants populations which is specifically grown with human intervention as a plant useful for feed, food, fuel or fibre or an ornamental plant. Crop plants may be plants which can be obtained by conventional breeding and optimization methods or by biotechnological, such as recombinant DNA techniques, genetic engineering methods, or gene editing methods such as CRISPR Cas or combinations of these methods, including the genetically modified plants (transgenic) or gene- edited (also named new genomic technologies) crop plants. Crop plants include also plant cultivars which are protectable and non-protectable by plant breeders’ rights, geno- or biotypes. Crop plants include the following species or genera: Alfafa, Anacardiaceae sp. (mango); beet, for example sugar beet and fodder beet; cereals, for example wheat, durum, barley, rye, oats, rice, maize, triticale and millet / sorghum; citrus fruit, for example oranges, lemons, mandarins, grapefruits and tangerines; cucurbits, for example pumpkin / squash, gherkins, calabashes, cucumbers and melons; fibre plants, for BCS246146 FC-Text / / EK-JK 2025-12-17 example coton, flax, hemp and jute, cannabis; Latex plants; Lauraceae sp. (e.g. avocado, cinnamon, camphor); legumes, for example beans, lentils, peas and soybeans, common beans and broad beans; Malvaceae sp. (e.g. okra, cocoa);Manihoteae sp. (for instance Manihot esculenta, manioc), oil crops, for example Brassica oil seeds such as Brassica napus (e.g. canola, rapeseed), Brassica rapa, B. juncea (e.g. (field) mustard) and Brassica carinata, Arecaceae sp. (e.g. oilpalm, coconut), mustard, poppies, Oleaceae sp. (e.g. olive tree, olives), sunflowers, castor oil plants; Papaveraceae (e.g. poppy), pome fruit for example apples, pears and quince, Ribesioidae sp., soft fruits for example strawberries, raspberries, blackberries, blueberries, red and black currant and gooseberry; Rubiaceae sp. (for instance coffee); Solanaceae sp. (e.g. tomatoes, potatoes, peppers, bell peppers, capsicum, aubergines, eggplant, tobacco), Stevia rebaudiana; stone fruit for example peaches, nectarines, cherries, plums, common plums, apricots; Theobroma sp. (for instance Theobroma cacao: cocoa); vegetables, for example spinach, letuce, Asparagaceae (e.g. asparagus), Cruciferae sp. (e.g. white cabbage, red cabbage, broccoli, cauliflower, Brussels sprouts, pak choi, kohlrabi, radishes, horseradish, cress and Chinese cabbage), onions, bell peppers, artichokes and chicory - including root chicory, endive or common chicory, leeks and onions; Umbelliferae sp. (e.g. carrots, parsley, celery and celeriac); Vitis sp. (for instance Vitis vinifera: grape vine, raisins, table grapes); Musaceae sp. (e.g. banana trees, bananas and plantations), nuts of various botanical taxa such as peanuts, Juglandaceae sp. (Walnut, Persian Walnut (Juglans regia), Buternut (Juglans), Hickory, Shagbark Hickory, Pecan (Carya), Wingnut (Pterocarya)), Fagaceae sp. (Chestnut (Castanea), Chestnuts, including Chinese Chestnut, Malabar chestnut, Sweet Chestnut, Beech (Fagus), Oak (Quercus), Stone-oak, Tanoak (Lithocarpus)); Betulaceae sp. (Alder (Alnus), Birch (Betula), Hazel, Filbert (Corylus), Hornbeam), Leguminosae sp. (for instance peanuts, peas and beans beans - such as climbing beans and broad beans), Asteraceae sp. (for instance sunflower seed), Almond, Beech, Buternut, Brazil nut, Candlenut, Cashew, Colocynth, Coton seed, Cucurbita ficifolia, Filbert, Indian Beech or Pongam Tree, Kola nut, Lotus seed, Macadamia, Mamoncillo, Maya nut, Mongongo, Oak acorns, Ogbono nut, Paradise nut, Pili nut, Pine nut, Pistacchio, Pumpkin seed, water Caltrop; soybeans (Glycine sp., Glycine max).

[0107] In one embodiment the crop plant is sensitive towards a certain crop protection product comprising one or more active ingredient.

[0108] Active ingredient means the component that controls, reduces, suppresses, repels or eliminates one or more phytopathogenic or undesired organisms including fungi, oomycetes, bacteria, virus, weed plants including broadleaf and grassy weed plant species, arthropods including insects, arachnids including mites, nematodes or foster plant health. Active ingredients include small molecules with a molecular weight of less than 1000 Daltons. Examples of active ingredients are natural or synthetic herbicides, safener, plant growth regulators, fungicides, and other pesticides (e.g., insecticides, nematicides, molluscicides, acaricides and the like) and / or biostimulants.

[0109] Crop protection products (CPPs means) a product that serves to protect crop plants or products of crop plants or both from phytopathogenic or undesired organisms including fungi, oomycetes, bacteria, virus, weed plants including broadleaf and grassy weed plant species, arthropods including insects, arachnids including mites, nematodes or prevent the effect thereof. Crop Protection Product are formulated to comprise at least one active ingredient and additional components such as adjuvants, surfactants, solvents, emulsifiers, stabilizers, inert ingredients, carriers etc. The application of CPPs typically involves dilution, where concentrated formulations are mixed with water to achieve the desired concentration for effective use. Tank mixing involves combining two or more CPPs in a single application to enhance efficacy and broaden the control scope.

[0110] In one embodiment the one or more agricultural field has been treated with soil residual crop protection products. Soil residual crop protection products means crop protection products which are or continue to be bioavailable in the soil to plants. BCS246146 FC-Text / / EK-JK 2025-12-17

[0111] A soil residual crop protection products means the following CPPs comprising one or more active ingredients selected from the group (A) comprising Pyrasulfotole , Tembotrione, Tolypyralate, Bicyclopyrone, Mesotrione, Topramezone, Florasulam, Imazamox, Imazethapyr, Imazapyr, Flucarbazone, Thiencarbazone-methyl, Triallate, Trifluralin, Ethalfluralin, Dicamba, 2,4-D Flumioxazin, Pyroxasulfone, Icafolin-Methyl, Clopyralid, Saflufenacil, Trifludimoxazin, Sulfentrazone, Indaziflam and Metribuzin, Isoxaflutole, Diflufenican, Aclonifen, s-Metolachlor, Pendimethalin, Acetochlor, and Atrazine

[0112] A soil residual crop protection products means the following CPPs comprising one or more active ingredients selected from this subgroup (A) comprising Pyrasulfotole , Tembotrione, Tolypyralate, Bicyclopyrone, Mesotrione, Topramezone, Florasulam, Imazamox, Imazethapyr, Flucarbazone, Thiencarbazone-methyl, Triallate, Trifluralin, Ethalfluralin, Dicamba, 2,4-D Flumioxazin, Pyroxasulfone, Icafolin-Methyl, Clopyralid, Saflufenacil, Trifludimoxazin, Sulfentrazone, Indaziflam and Metribuzin.

[0113] A soil residual crop protection products means the following CPPs comprising one or more active ingredients selected from the group comprising Pyrasulfotole , Tembotrione, Bicyclopyrone, Mesotrione, Topramezone, Florasulam, Imazamox, Imazethapyr, Imazapyr, Flucarbazone, Thiencarbazone-methyl, Dicamba, 2,4-D Flumioxazin, Pyroxasulfone, Icafolin-Methyl, Clopyralid, Saflufenacil, Trifludimoxazin, Sulfentrazone, Indaziflam, Isoxaflutole, Diflufenican, Aclonifen, s- Metolachlor, Pendimethalin, Acetochlor, and Atrazine.

[0114] In one embodiment crop protection products means Pyrasulfotole, Tembotrione, Bicyclopyrone, Mesotrione, Topramezone, Florasulam, Imazamox, Imazethapyr, Imazapyr, Flucarbazone, Thiencarbazone-methyl, Dicamba, 2,4-D Flumioxazin, Pyroxasulfone, Icafolin-Methyl, Clopyralid, Saflufenacil, Trifludimoxazin, Sulfentrazone, Indaziflam, Isoxaflutole, Diflufenican, Aclonifen, s- Metolachlor, Pendimethalin, Acetochlor, and Atrazine

[0115] In one embodiment crop protection products means Pyrasulfotole.

[0116] In one embodiment crop protection products means Tembotrione.

[0117] In one embodiment crop protection products means Tolypyralate.

[0118] In one embodiment crop protection products means Bicyclopyron.e

[0119] In one embodiment crop protection products means Mesotrione.

[0120] In one embodiment crop protection products means Topramezon.e

[0121] In one embodiment crop protection products means Florasulam.

[0122] In one embodiment crop protection products means Imazamox.

[0123] In one embodiment crop protection products means Imazethapyr.

[0124] In one embodiment crop protection products means Imazapyr.

[0125] In one embodiment crop protection products means Flucarbazone.

[0126] In one embodiment crop protection products means Thiencarbazone-methyl.

[0127] In one embodiment crop protection products means Triallate.

[0128] In one embodiment crop protection products means Trifluralin.

[0129] In one embodiment crop protection products means Ethalfluralin.

[0130] In one embodiment crop protection products means Dicamba.

[0131] In one embodiment crop protection products means 2,4-D.

[0132] In one embodiment crop protection products means Flumioxazin.

[0133] In one embodiment crop protection products means Pyroxasulfone. BCS246146 FC-Text / / EK-JK 2025-12-17

[0134] In one embodiment crop protection products means Icafolin-Methyl.

[0135] In one embodiment crop protection products means Clopyralid.

[0136] In one embodiment crop protection products means Saflufenacil.

[0137] In one embodiment crop protection products means Trifludimoxazin.

[0138] In one embodiment crop protection products means Sulfentrazone.

[0139] In one embodiment crop protection products means Indaziflam.

[0140] In one embodiment crop protection products means Metribuzin.

[0141] In one embodiment crop protection products means Isoxaflutole.

[0142] In one embodiment crop protection products means Diflufenican.

[0143] In one embodiment crop protection products means s-Metolachlor.

[0144] In one embodiment crop protection products means Aclonifen.

[0145] In one embodiment crop protection products means Pendimethalin.

[0146] In one embodiment crop protection products means Acetochlor.

[0147] In one embodiment crop protection products means Atrazine.

[0148] In the second step the fraction of one or more vegetation classes on the basis of the one or more digital images is calculated by utilizing machine learning and the associated algorithm to classify each pixel of the digital image as either living vegetation, dead vegetation, or other.

[0149] Vegetation classes represent the different classes of groundcover in an agricultural area. Groundcover means the vegetation comprising plants including crop plants or weed plants or both including all plant parts present on that location or agricultural area. Typical examples are living vegetation meaning any plants capable of growing, dead vegetation or residue meaning plants no longer capable of growing (eg stubble) or no vegetation or soil meaning no plant is present or layer of material applied to the surface of soil eg mulch of natural or artificial origin.

[0150] In one embodiment at least 1 to 20 images per ha are used for calculating the fraction of one or more vegetation classes.

[0151] In one embodiment the fraction of vegetation classes is based on the relative area covered by the vegetation including the calculating the canopy height using the canopy height for classifying the vegetation into dead vegetation / residue and living vegetation.

[0152] In a third step additional agronomic data is received.

[0153] Agronomic data means any of the following: identification data (for example, acreage, field name, field identifiers, geographic identifiers, boundary identifiers, crop identifiers, and any other suitable data that may be used to identify farm land, such as a common land unit (CLU), lot and block number, a parcel number, geographic coordinates and boundaries, Farm Serial Number (FSN), farm number, tract number, field number, section, township, and / or range), (b) harvest data (for example, crop plant type, crop plant variety, crop plant rotation, whether the crop plant is grown organically, harvest date, Actual Production History (APH), expected yield, yield, crop plant price, crop plant revenue, grain moisture, tillage practice, and previous growing season information), (c) soil data (for example, type, composition, pH, soil organic matter (SOM), cation exchange capacity (CEC)) soil type, soil components including silt, sand, clay, loam; (d) planting data (for example, planting date, seed(s) type, relative maturity (RM) of planted seed(s), seed population), (e) fertilizer data (for example, nutrient type (Nitrogen, Phosphorous, Potassium), application type, application date, amount, source, method), (f) chemical application data (for example, pesticide, herbicide, fungicide, other substance or mixture of substances intended for use as a plant regulator, defoliant, or desiccant, application date, amount, source, method), BCS246146 FC-Text / / EK-JK 2025-12-17

[0154] (g) irrigation data (for example, application date, amount, source, method), (h) weather data (for example, precipitation, rainfall rate, predicted rainfall, water runoff rate region, temperature, wind, forecast, pressure, visibility, clouds, heat index, dew point, humidity, snow depth, air quality, sunrise, sunset), (i) imagery data (for example, imagery and light spectrum information from an agricultural apparatus sensor, camera, computer, smartphone, tablet, unmanned aerial vehicle, planes or satellite), (j) scouting observations (photos, videos, free form notes, voice recordings, voice transcriptions, weather conditions (temperature, precipitation (current and overtime), soil moisture, crop plant growth stage, wind velocity, relative humidity, dew point, black layer)), and (k) soil, seed, crop plant phenology, pest and disease reporting, and predictions sources and databases.

[0155] In one embodiment agronomic data comprises soil data, in particular soil components, pH of soil, soil organic matter (SOM), cation exchange capacity (CEC); application parameters of CPP applications, including application type (spraying, dusting, injecting), application time including bumdown application.

[0156] In one embodiment the agronomic data comprises application parameters of one or more crop protection product, soil data, weather data.

[0157] A burndown application means one or more applications of a crop protection product, in particular a broad spectrum herbicide at the beginning of a growing season before seeding and / or emergence of the crop plant (BBCH 0).

[0158] An In Crop application means one or more applications of a crop protection product, in particular one or more herbicides in the growing season before seeding the crop plant (BBCH 8 to 99)

[0159] A Post Harvest Application means one or more applications of a crop protection product, in particular one or more herbicides after the growing season (after BBCH 99)

[0160] In no-till farming, crop seeds are planted directly into the soil covered by groundcover without tilling practices like ploughing. In no till farming bumdown application are used for vegetation control.

[0161] In a fourth step a risk value for crop plant phytotoxicity for the one or more subsequent crop plants to be planted or planted in the agricultural area is calculated based on the fraction of one or more vegetation classes and the agronomic data;

[0162] Crop plant phytotoxicity means one or more adverse effect on a crop plant's growth, physiology or metabolism, measurement of phytotoxicity of the visual injury, changes in color, appearance, stunting, crop plant stand, thinning, any of these effects may be assessed in trials or in a commercial field.

[0163] In a fifth step an agronomic recommendation regarding crop plant phytotoxicity risk is provided.

[0164] An agronomic recommendation may comprise a time, an amount of and / or a type of one or more CPPs to be applied to an agricultural area at one or more locations. In one embodiment the agronomic recommendation is configured to control an agricultural device, e.g., an agricultural vehicle or an agricultural robot, including a smart spraying system, to apply the specified amount and / or type of the CPP at a specific time period to one or more agricultural areas at one or more specific locations. The agronomic recommendation may also comprise one or more recommended time points for planting and / or harvesting an agricultural area at one or more locations with the selection of the plurality of crops. Said agronomic recommendation and / or agronomic control data is generated based on the risk value for crop plant phytotoxicity. The agronomic recommendation for planting a field may be used, e.g., to control a smart seeding system. In one embodiment the agronomic recommendation for applying one or more CPPS may be made based on the predicted time for a certain growth stage of the one or more crop plants on the one or more agricultural areas or locations. The agronomic recommendation may be provided in different ways. One Example is show in Figure 4 disclosing the user interface of the computationally implemented method in form of an app. Digital images have been used for the indicated specific field (Field: PYS Demo 1) to provide the relative ground cover at the time of application, additional agronomic data like precipitation within a certain time period, soil BCS246146 FC-Text / / EK-JK 2025-12-17 properties like pH or Soil Organic Matter, application date and concentration of the crop protection product, and applied crop protection product, planned cropped may be acquired either manually or automatically. The recommendation based on the crop plant phytotoxicity risk may be provided qualitatively (eg Carry over Risk acceptable, non acceptable, avoid) or on a numerical scale. It is also possible to provided that recommendation based on the calculation of different time points on which the planting is foreseen.

[0165] In one embodiment the method further comprises the step of generating a script for the application of one or more crop protection product to that agricultural location.

[0166] A script means a machine -readable set of instructions configured to control an agricultural device.

[0167] A method according to any of claims 1 to 4, wherein the vegetation classes are comprised of the following classes: living vegetation (canopy), dead vegetation (residue) and no vegetation (soil).

[0168] In one embodiment an agronomic recommendation or a script is generated for planting the subsequent crop.

[0169] In one embodiment an agronomic recommendation or a script is generated for the application of one or more crop protection product to that agricultural location.

[0170] In one embodiment the agricultural field has been subjected to no-till farming in the current or previous cropping cycle.

[0171] Examples

[0172] Some implementations of the present disclosure will be described more fully with reference to the accompanying examples, in which some, but not all implementations of the disclosure are shown. Indeed, various implementations of the disclosure may be embodied in many different forms and should not be construed as limited to the implementations described in the examples; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0173] Examples

[0174] Example 1

[0175] Huskie PRE or Infinity, two crop protection products, comprise the herbicide Pyrasulfotole and Bromoxynil and is used for weed control in particular of broadleaf weed species like Kochia in cereal fields. Pyrasulfotole breakdown in soil is dependent on factors like microbial decomposition, soil type due to adsorption to soil colloids, soil pH and plant / residue interception which is reflected in the groundcover. Therefore when planting crops for the season after a Pyrasulfotole application certain recropping intervals for certain crops need to be observed. For example for Huskie PRE the recropping interval with respect to lentils is 22 months.

[0176] In 2023 field trials at five different locations across the Canadian provinces Alberta and Saskatchewan with different soil types and characteristic such as soil texture (loam, silt loam clay loam), soil organic matter, pH and Cation Exchange Capacity (CEC), where in year zero either a cereal (CER) or oilseed rape (OSR) was planted and harvested, in the first year (2023) a cereal, eg wheat, was planted, and in the second year (2024) lentils were planted.

[0177] Pyrasulfotole (PYS) and Bromoxynil (BXD) were used in two concentrations (Concentration 1: PYS 25 grams / ha: BXD 280 grams / ha; concentration 2: PYS 50 grams / ha: BXD 560 grams / ha) plus a negative control without any treatment in a bumdown application at BBCH stage 00 of the first year crop in the first year. The application was therefore on the groundcover of the crop of year zero. All trials comprised four replicates, in addition no till and till practice were comparedin a split plot with tillage (low groundcover) and no till (high groundcover) being assessed. . The groundcover was assessed using digital imaging at the time of spray application in the first year of the trials. BCS246146 FC-Text / / EK-JK 2025-12-17

[0178] Figure 3A shows the field trial design crop were planted in defined cells in a grid design of duplicated rows 100 to 400 and column 1 to 7 resulting in a total number 56 of cells. Each cell was split into no- till and till separated by an alley. The red lines indicate how the operator carrying the mobile device equipped with LiDAR technology moved in the middle of the cells along the columns. LiDAR signals were continuously received during the movement along the columns.

[0179] Figure 4 disclose the user interface of the app providing the recommendation for planting lentil. Digital images have been used for the indicated specific field (Field: PYS Demo 1) to provide the relative ground cover at the time of application, additional agronomic data like precipitation within a certain time period, soil properties like pH or Soil Organic Matter, application date and applied crop protection product (Huskie PRE), planned crop (lentils) may be acquired either manually or automatically. The recommendation based on the crop plant phytotoxicity risk may be provided qualitatively (eg Carry over Risk acceptable, non acceptable, avoid) or on a numerical scale. It is also possible to provide that recommendation based on the calculation of different time points on which the planting is foreseen. Here the time of application was the 10 May 2023, the date of forecast is 3 April 2024 at which with an acceptable carry over risk lentil may be planted. By using this time and location specific prediction planting of lentil may already safely performed at 11 months after the last application of Huskie PRE.

[0180] Table 1 Groundcover (%) at burndown application on the ground cover of the crop of year zero

[0181] The percentage of ground cover is a mean of the percentage of groundcover at concentration 1 and 2.

[0182] No till practice results in approximately two times of groundcover compared to till practice.

[0183] Table 2 Maximum Crop Injury of the second year crop lentils

[0184] The bum down application for the first year crop, the cereal was performed on 15 June 2023. Lentils were seeded on 15 May 2024 across five locations, so about 11 months later. Phytotoxicity was rated at 7, 14, 35 and 56 days after emergence. The Canadian Weed Science Society states that up to 10 % of phytotoxicity done by assessment of the crop showing eg symptoms like slight discoloration or stunting are acceptable.

[0185] The table provides the maximum value of phytotoxicity detected of all four assessments. BCS246146 FC-Text / / EK-JK 2025-12-17

[0186] Phytotoxicity in no-till plots (with increased groundcover) is consistently lower than in tilled plots - especially in higher phytotoxicity risk trials. Table 3 Yields of the second year crop lentils (t / ha at 14 % moisture)

[0187] Yields of lentils, which were planted already 11 months after Pyrasulfotole application are comparable with yields on field non treated with Pyrasulfotole.

[0188] Table 4 Groundcover (%) at the two to three leaf crop stage application of a pyrasulfotole containing herbicide

[0189] The percentage of ground cover is a mean of the percentage of groundcover at concentration 1 and 2.

[0190] No till practice results in approximately two times of groundcover compared to till practice. BCS246146 FC-Text / / EK-JK 2025-12-17

[0191] Table 5 Maximum Crop Injury of the second year crop lentils

[0192] The two to three leaf application for the first year crop, the cereal was performed in 2023 about 9 to 10 months prior to seeding lentils in 2024 across five locations. Phytotoxicity was rated at 7, 14, 35 and 56 days after lentil emergence. The Canadian Weed Science Society states that up to 10 % of phytotoxicity done by assessment of the crop showing eg symptoms like slight discoloration or stunting are acceptable.

[0193] The table provides the maximum value of phytotoxicity detected of all four measurements. Phytotoxicity in no-till p ots (with increased groundcover) is lower than in tilled plots - especially in higher phytotoxicity risk trials.

[0194] Table 6 Yields of the second year crop lentils (t / ha at 14 % moisture)

[0195] Yields of lentils, which had been planted already 9 to 10 months after the Pyrasulfotole application are comparable with yields on field non treated with Pyrasulfotole at concentration 1 (registered use rate)

Claims

BCS246146 FC-Text / / EK-JK 2025-12-17CLAIMS1. Computationally implemented method comprisingReceiving one or more digital images of one or more locations of an agricultural area;Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images;Receiving additional agronomic data ;Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

2. A method according to claim 1 in which the agronomic recommendation comprises planting a subsequent crop or applying a crop protection product.

3. A method according to claim 1 or 2 wherein the agronomic data comprises application parameters of one or more crop protection product, soil data, weather data.

4. A method according to any of claims 1 to 3, wherein the vegetation classes are comprised of the following classes: living vegetation (canopy), dead vegetation (residue) and no vegetation (soil).

5. A method according to any of claims 1 to 4, further comprising generating a script for planting the subsequent crop.

6. A method according to any of claims 1 to 4, further comprising generating a script for the application of one or more crop protection product to that agricultural location.

7. A method according to any of claims 1 to 6, wherein the agricultural field has been subjected to no-till farming in the current or previous cropping cycle.

8. A method according to any of claims 1 to 7, wherein the agricultural field has been treated with soil residual crop protection products.

9. A computer program product comprising instructions which, when the program is executed by a computing system, cause the computing system to carry out the steps comprising:Receiving the one or more digital images of one or more locations of an agricultural area;Calculating the fraction of one or more vegetation classes on the basis of the one or more digital images;Receiving additional agronomic data;Calculating based on the fraction of one or more vegetation classes and the agronomic data a risk value for crop plant phytotoxicity on the one or more subsequent crop plants to be planted or planted in the agricultural area;Providing an agronomic recommendation regarding crop plant phytotoxicity risk.

10. A computer program product according to claim 8 in an additional step the agronomic recommendation comprises planting a subsequent crop or applying a crop protection product.

11. A computer program product according to claim 9 or 10, in which the agronomic data comprises application parameters of one or more crop protection product, soil data, weather data.BCS246146 FC-Text / / EK-JK 2025-12-1712. A computer program product according to any of claims 9 to 11, wherein the vegetation classes are comprised of the following classes: living vegetation (canopy), dead vegetation (residue) and no vegetation (soil).

13. A computer program product according to any of claims 9 to 12, further comprising a step for generating a script for planting the subsequent crop.

14. A computer program product according to any of claims 9 to 12, further comprising a step for generating a script for the application of one or more crop protection product to that agricultural location.

15. A computer program product according to any of claims 9 to 14, wherein the agricultural field has been subjected to no-till farming in the current or previous cropping cycle.

16. A computer program product according to any of claims 9 to 15, wherein the agricultural field has been treated with soil residual crop protection products.

17. A computer system comprising a computer program product according to any of claims 9 to 16, or a computationally implemented method according to any of claims 1 to 8 and a device or app.

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