COMPUTER-IMPLEMENTED METHOD AND SYSTEM FOR PROVIDING AT LEAST ONE MIGRATION RISK INDEX, USE OF SAID MIGRATION RISK INDICES, COMPUTER-IMPLEMENTED METHOD FOR PROVIDING A MIGRATION RISK MAP OF A FIELD, AND METHOD FOR APPLYING A PRODUCT TO AN AGRICULTURAL FIELD

Abstract

A computer-implemented method for providing at least one migration risk index, comprising the steps: providing soil data for a location, comprising at least information about the soil composition at that location (S10); providing climate data for that location, comprising at least historical precipitation data for that location (S20); providing a soil mobility model for a product, wherein the soil mobility model is configured to calculate migration data of the product at that location based on the soil data and climate data (S30); and determining at least one migration risk index based on the migration data and representing a risk of that product migrating downwards to a lower soil layer at that location (S40).

Description

27389 COMPUTER-IMPLEMENTED METHOD TO PROVIDE AT LEAST ONE MIGRATION RISK INDEX TECHNICAL FIELD This disclosure relates to a computer-implemented method for providing at least one migration risk index, a use of such migration risk indices to generate a migration risk map of a field, a use of such migration risk indices to provide control data for monitoring farm equipment, a system for providing at least one migration risk index, a computer-implemented method for such migration risk mapping of a field, farm equipment, and a computer program element. TECHNICAL BACKGROUND In agriculture, some products are used that, if possible, should not reach the groundwater, or should do so only in the smallest possible quantities. For example, pesticides are used to protect plants against pests, such as aphids, and it is preferred, and sometimes required, that these pesticides or their breakdown products (e.g., irrelevant metabolites) do not reach the groundwater. This also applies, for example, to liquid manure, nitrates, herbicides, fungicides, and fertilizers. It was discovered that there is a need to provide means by which, for example, a farmer applying such products to a field can prevent these degradation products from entering a deeper layer of soil or groundwater. SUMMARY OF THE INVENTION Therefore, it is an object of the present invention to provide means by which, for example, a farmer applying such products to a field can prevent these degradation products from entering a deeper layer of soil or groundwater. These and other objects, which are evident from reading the present description, are addressed by the independent claims. The dependent claims relate to preferred embodiments of the 1512092 of 14 invention. Pursuant to a first aspect of this disclosure, a computer-implemented method is provided for providing at least one migration risk index, comprising the following steps: providing soil data for a location, comprising at least information about the soil composition at that location; providing historical climate data for that location; providing a soil mobility model for a product, wherein the soil mobility model is configured to calculate migration data of the product at that location based on the soil data and climate data; and determining at least one migration risk index based on the migration data and representing a risk that the product will migrate downward to a lower soil layer at that location. The term "migration risk index" is defined herein as a variable comprising at least two stages, and preferably more. These stages indicate risk levels of a product reaching a lower soil layer and / or groundwater, such as high risk, moderate risk, low risk, no risk, etc. The respective risk levels may consist of numbers, letters, or phrases. The term "soil data" is understood in a broad sense herein and may include all data relating to soil properties relevant to solute transport, such as texture, particle size distribution, organic carbon content, density, soil type, soil layer height, number of layers, etc. The term "soil composition" includes the different contents of soil types, stones or other materials, the spatial distribution of these contents, etc.The term "location" is also understood in a broad sense herein and includes areas of any size, shape, and elevation profile. The location may be a portion of an agricultural field or the entirety of the agricultural field. The expression "climate data" is understood in a broad sense herein and includes daily precipitation amounts, precipitation intervals, air temperatures, evaporation and transpiration, wind speeds, solar radiation, gradients and intervals, and durations of the aforementioned parameters, etc. The expression "climate data" may include historical, current, or future climate data. However, it is preferred that climate data include only historical climate data. The expression "historical climate data" should be understood in a broad sense herein and includes climate data from the past. Preferably, the expression "historical climate data" includes... 1512092 of 14 present case daily climate data for the last week, last two weeks, last month, last 3 months, last 6 months, last season and / or last year. The soil mobility model describes the fate and behavior of a product in the soil, such as degradation, sorption and leaching, based on climate and soil data for its location. The soil mobility model can be an equation-based model. The soil mobility model can be based on physical equations, statistical equations derived from experiments or neural networks. The term product is understood in a broad sense in this case and includes all types of products that should not migrate to deeper soil layers and / or groundwater, such as plant treatment agents, pesticides, fertilizers, fungicides, etc. (e.g., metazachlor, bentazon and imazamox).The term "migration data" is understood in a broad sense in this case and includes data on the product's mobility in the soil, such as soil movement, penetration depth, and spread. Preferably, the risk involves the product migrating downwards into groundwater and leaching into it. This disclosure is based on the discovery that products applied to a specific agricultural field location can leach into and contaminate groundwater. However, these products are necessary to protect plants and / or increase plant yields. Therefore, it is advantageous for a farmer to be aware of the risks associated with applying a product to a particular field location. The risk or likelihood of a product leaching into groundwater depends on interactions between the product, the soil at the location, and climatic conditions. These interactions depend on product properties, such as density, viscosity, and degradation characteristics, and soil properties, such as soil texture and organic carbon content, as well as climatic conditions, such as temperature and precipitation levels.This disclosure provides a soil mobility model, which describes the interactions and provides a migration risk index for the product. It is important to note that a separate soil mobility model may be provided for each product. The migration risk index can guide the farmer on whether and / or how to apply the product at the field location (e.g., whether to apply, application rates, application intervals). The migration risk index can advantageously simplify plant treatment at the field location. 1512092 of 14 migration risk can advantageously increase plant yield. The migration risk index can advantageously protect groundwater from contamination by products. In one embodiment, migration data comprises at least soil velocity / mobility data of the product. The term soil mobility describes the rate at which a product spreads through the soil. Soil velocity / mobility can be used in conjunction with soil height to determine the time required for the product to reach that soil height before leaching into groundwater. Soil mobility can then be used to determine the migration risk index. Soil mobility can advantageously contribute to a precise determination of the migration risk index and, therefore, to increased plant yield along with greater groundwater protection. In one embodiment, the soil mobility model is based on the physicochemical interaction of the product with the soil and / or the product's degradation characteristics. Physicochemical interactions include the product's flow behavior in the soil, its adhesion behavior in the soil, its diffusion behavior in the soil, its chemical reaction with the soil, and so on. Physicochemical interactions can contribute advantageously to a precise determination of the migration risk index and, therefore, to increased plant yield along with greater groundwater protection. The degradation characteristic, in this case, describes the product's degradation over time. Product degradation characteristics can be used in combination with the product's soil mobility to accurately determine the migration risk index. In one implementation, the climate data also includes future precipitation (i.e., precipitation levels over a given period) for that location. Future precipitation values ​​cover periods of hours, days, or weeks, among others. By considering future precipitation, it is possible to increase the accuracy of the soil mobility model and, therefore, the accuracy of the migration risk index determination, which can improve plant yields while also better protecting groundwater. In one embodiment, the location is part of a field, where the field preferably comprises more than one location, and / or the location is defined 1512092 of 14 using geographic data, preferably size, shape, and geographic coordinates. By dividing an agricultural field into several locations, it is possible to determine a distribution of migration risk indices, rather than an imprecise average value. This can contribute to increased plant yield in the field along with greater protection of groundwater. In one embodiment, the migration risk index comprises at least two stages (e.g., low and high risk). The migration risk index is not limited to two stages or terms such as low and high risk; other codes, such as colors or values, are also suitable. These stages can help simplify the interpretation of migration risk indices and thus increase the ease of use and effectiveness of risk determination or assessment. In one embodiment, the method further comprises determining a product application rate for the location based on the migration risk index. Determining the application rate from the migration risk index avoids the calculation difficulties that typically require a farmer or someone with a mid-level agricultural skill set. Therefore, determining the application rate simplifies the complex process and reduces errors, thereby increasing the effectiveness of the plant treatment, which can lead to higher plant yields along with greater protection of groundwater. In one embodiment, the product comprises agrochemicals, preferably pesticides, fungicides, and / or fertilizers. The method can be applied to various products and, therefore, to different activities in the plant growth cycle (e.g., weed, fungicide, and insect management). Thus, all growth stages and corresponding treatment activities can be improved by the method, thereby increasing plant yield and enhancing groundwater protection. Another aspect of this disclosure relates to the use of migration risk indices determined according to a computer-implemented method to provide at least one migration risk index for generating a migration risk map of a field. A migration risk map of a field provides a distribution of the individual migration risk indices and can contribute to the selection of appropriate equipment (e.g., size and accuracy of product discharge units) for field treatment. The migration risk map can contribute to further field analysis (e.g., historical changes in migration risk indices, 1512092 of 14 detection of incorrect strategies at various stations, etc.). Another aspect of this disclosure relates to the use of migration risk indices determined according to a computer-implemented method to provide at least one migration risk index for monitoring agricultural equipment, where the equipment is preferably a sprayer vehicle. The monitoring data may include geographic data of the location in the field and application rate limits of the product for that location. The agricultural equipment may include a GPS to detect the current position and to apply the desired application rate of the product to the desired location. Therefore, the monitoring data can increase efficiency by reducing and optimizing the amount of product applied to the field location and further protect groundwater. Another aspect of this disclosure relates to a system for providing at least one migration risk index, comprising: at least one receiving interface for receiving soil data for a location, comprising at least information about the soil composition at that location; at least one receiving interface for receiving climate data for that location, comprising at least historical precipitation data for that location; at least one processing unit configured to run a soil mobility model for a product, wherein that soil mobility model is configured to determine migration data of the product at that location based on the soil data and climate data;At least one processing unit configured to determine at least one migration risk index based on migration data, representing the risk of the product migrating downwards to a lower soil layer. The system can be a CPU in an agricultural equipment controller (e.g., a sprayer), a desktop computer, a smartphone, a tablet, or a virtual machine hosted in a cloud application. The system can be used by a farmer and can guide them in increasing plant yields while also protecting groundwater. This system can advantageously increase the efficiency of product application in agricultural fields. This can be beneficial in reducing the risk of groundwater leaching and thus ensuring responsible management and the application of sustainable crop protection. Another aspect of this disclosure relates to a computer-implemented method for providing a migration risk map of a field, which Step 1512092 of 14 comprises the following steps: determining migration risk indices for locations within a field according to a computer-implemented method to provide at least one migration risk index; generating a migration risk map based on the determined migration risk indices. In this context, the computer-implemented method preferably comprises determining an application rate for the product for the locations within the field; and generating an application rate map for the product for the field based on the determined application rates. The migration risk map and the application rate map can contribute to increased plant yields along with greater groundwater protection. This can further enhance sustainability and responsible environmental management. Another aspect of this disclosure relates to agricultural equipment configured to be controlled using control data generated from a migration risk map provided as explained above. This control data can be used in conjunction with the equipment's GPS to dispense the product very precisely, thereby increasing plant yield and enhancing groundwater protection. This can further improve sustainability and promote responsible environmental management. Another aspect relates to a method for applying a product in an agricultural field, comprising the following steps: providing control data generated based on a migration risk map provided by a method as explained above; applying a product in the field by means of agricultural equipment controlled by the control data. Another aspect of this disclosure relates to a computer program element that, when executed by a processor, is configured to carry out the method for providing a migration risk map of a field. Therefore, the computer element can be stored in a computer unit, which can also be part of an embodiment. The computer unit can be configured to perform or induce the performance of the steps of the method described above. Furthermore, it can be configured to operate the components of the system described above. The computer unit can be configured to operate automatically and / or execute user commands. A computer program can be loaded into the working memory of a data processor. Therefore, the data processor can be equipped to carry out the method according to one of the embodiments. 1512092 of the preceding 14. This example embodiment of the present disclosure includes both a computer program that uses the present disclosure from the outset and a computer program that, through an update, converts an existing program into one that uses the present disclosure. Furthermore, the computer program element may be capable of providing all the steps necessary to complete the procedure of an example embodiment of the method as described herein. According to another example embodiment of the present disclosure, a computer-readable medium, such as a CD-ROM, a USB device, or the like, is presented, wherein the computer-readable medium has a stored computer program element as described in the preceding paragraph.A computer program may be stored and / or distributed on a suitable medium, such as optical storage media or solid-state media supplied with, or as part of, other hardware, but may also be distributed in other ways, such as via the Internet or other wired or wireless telecommunications systems. However, the computer program may also be presented over a network, such as the World Wide Web, and downloaded into the working memory of a data processor on that network. According to another example embodiment of this disclosure, a means is provided for making a computer program element available for download, wherein the computer program element is arranged to carry out a method according to one of the embodiments of this disclosure described above. BRIEF DESCRIPTION OF THE DRAWINGS The following disclosure is described by way of example with reference to the accompanying figures, where Figure 1 is a schematic overview of the steps of a method according to this disclosure; and Figure 2 is a schematic view of a sprayer that may be used as agricultural equipment according to this disclosure. DETAILED DESCRIPTION OF THE FORM OF IMPLEMENTATION Figure 1 is a schematic view of a method according to this disclosure. An example of the order of steps according to this disclosure is explained below. However, the order provided is not 1512092 of 14 mandatory, that is, all or several stages can be carried out in a different order or simultaneously. The method described below can be summarized as follows. In the first stage, soil data for a field are provided. In the second stage, climate data for the field are provided. In the third stage, a soil mobility model is provided for a product (e.g., a specific herbicide) to be applied to the field. This soil mobility model is used to determine product migration data (e.g., product mobility in the soil) based on the soil and climate data. In the fourth stage, a migration risk index is determined based on the migration data. In the fifth stage, a migration risk map is generated based on the determined migration risk indices. Finally, an application rate map is generated. In an S10 stage, soil data is provided for one or more locations within a field. Soil data can include all information pertaining to soil, such as density, soil composition, soil type, soil layer height, number of layers, roughness, diffusion coefficients, moisture content, stone content, adhesion forces, moisture storage capacity, etc. Soil composition can include the different contents of soil types, stones or other materials, spatial distribution of these contents, etc. Soil data can be provided from a database (e.g., a Ministry of Agriculture database) or by the farmer. In an S20 stage, climate data is provided for the field. This climate data may include precipitation values ​​and durations / intervals, temperatures, wind speeds, solar radiation values ​​and durations / intervals, etc. The climate data may include historical, current, and / or future climate data. However, it is preferred that the climate data include only historical climate data. The climate data may be provided from a commercial climate database, national meteorological services, or research institutes. In an S30 stage, a soil mobility model is provided for a product. The soil mobility model calculates product migration data at that location based on soil and climate data. It receives soil and climate data as input and determines an output, i.e. 1512092 of 14 migration data. Migration data includes soil mobility and product propagation distances in the soil. In an S40 stage, a product migration risk index is determined for each field location. The migration risk index is based on migration data and provides a representative risk or probability that the product will migrate downwards to a lower soil layer at that location. To determine the risk or probability, factors such as soil mobility and soil layer height (i.e., transmission distance to reach groundwater) are compared to the product's degradation time. If the transmission time from the soil layer height is greater than the product's degradation time, the risk is low; otherwise, it is high. Many parameters affect soil mobility and product propagation distances, and the example above is provided for illustrative purposes only.The migration risk index of a product for a field location is an assessment of migration data compared to the circumstances of the field location (i.e., soil data and climate data), which includes interactions between them. In an S50 stage, a field migration risk map is generated. This map includes the individual migration risk index for each location and displays the distribution of this index across the field. The migration risk map can be provided to a farmer as a basis for further field analysis, either in conjunction with the product or in comparison to other products. Additionally, the migration risk map can be further processed to determine control data for agricultural equipment (e.g., a smart sprayer), where this control data may include application rate limits for the product. In an S60 stage, an application rate map is generated. This map includes product limits and additional quantities of the product required for different field locations. The application rate map serves as a control input for agricultural equipment (e.g., a smart sprayer). The smart sprayer may have multiple spray units, each controlled independently, and different product rates are applied to different field locations based on the current location and the application rate map. The application rate can be determined based on the required quantities of the product (i.e., the desired application rate). 1512092 of 14 The limits are due to the migration risk index and safety values. In this case, the safety values ​​represent application rate distances from the limits to reduce the risk of a product leaching into groundwater. The application rate map can also be used as a basis for analysis by the farmer and can be displayed, for example, on a screen in an agricultural vehicle. Figure 2 is a schematic view of a 20 sprayer that may be used as agricultural equipment in accordance with this disclosure. Figure 2 shows a tractor with sprayer 20 for applying a pesticide, such as a herbicide, fungicide, or insecticide, to a field 10 with plants 11. The sprayer 20 can be detachably attached or mounted directly onto the tractor. The sprayer 20 comprises a boom with multiple nozzles 22 arranged along the boom. The nozzles 22 can be fixed or movable along the boom at regular or irregular intervals. Each nozzle 22 includes a controllable valve for regulating the fluid release from the nozzles 22 into the field. One or more tanks 24 are in fluid connection with nozzles 22 via tubes 26. Each tank 24 contains one or more components of the fluid mixture to be distributed in the field 10. It may include chemically active or inactive components such as a herbicide mixture, components of a herbicide mixture, a selective herbicide for specific weeds, a fungicide, a fungicide mixture, a fungicide and plant growth regulator mixture, a plant growth regulator, water, oil, or similar substances. Each tank 24 may also include a controllable valve to regulate the release of fluids from the tank 24 to the tubes 26. This arrangement allows for control of the mixture released in the field. A control 28 on the sprayer 20 controls the tank and / or nozzle valves 22 based on the application rate map and / or migration risk map. This disclosure describes a preferred embodiment and provides examples. However, persons of average skill can understand and implement other variations and put the claimed invention into practice by studying the drawings, this disclosure, and the claims. It is particularly noteworthy that steps S10 to S60 can be performed in any order; that is, the present invention is not limited to a specific sequence of these steps. Furthermore, it is not necessary that the different steps be 1512092 of 14 are carried out in a specific location or in a single location; that is, each of the steps can be carried out in a different location using different data processing equipment / units. In the claims, as well as in the description, the expression "comprising" does not exclude other elements or steps, and the indefinite article "a" does not exclude plurality. A single element or any other unit can perform the functions of various entities or items mentioned in the claims. The mere fact that some measures are mentioned in different dependent claims does not mean that a combination of these measures cannot be used conveniently. 1512092 of 14 Reference signs S10 Provide soil data S20 Provide climate data S30 Provide a soil mobility model S40 Determine at least one migration risk index S50 Generate a migration risk map S60 Generate an application rate map 10 Field 11 Plant 20 Sprayer 22 Nozzle 24 Tank 26 Pipe 28 Control 1512092 of 14 Federico Aulmann - 20219535830 Digitally signed by PORTALTRAM ITES - INPI Date: 2021.09.17 14:32:50 -03:00 Reason: Digitally Signed by the INPI Location: Buenos Aires, Argentina 1512092

Claims

1. A computer-implemented method for providing at least one migration risk index, characterized in that it comprises the steps of: providing soil data for a location, comprising at least information on the soil composition at that location (S10); providing meteorological data for that location, comprising at least historical rainfall data for that location (S20); providing a soil mobility model for a product, wherein the soil mobility model is configured to calculate migration data of the product at that location based on the soil data and the meteorological data (S30); and determining at least one migration risk index based on the migration data and representative of a risk that the product will migrate to a lower soil layer at that location (S40). Thirteen claims follow.