Prediction of residues of plant protection agents in harvested products
The present invention relates to the prediction of residues of plant protection agents in plants or plant parts which are intended for human or animal consumption, preferably in vegetables and/or fruit. The present invention also relates to a method, a device, a system and a computer program product for predicting residues of plant protection agents.
1 . A device for predicting crop protection product residues in plants or parts of plants, the device comprising at least one processor configured to:
generate a first interface for display at a computer that displays one or more interactive menus that allows user selection of at least a type of crop plant, wherein the interface includes a virtual map element to allow a user clicking on the virtual map element by means of finger movements to enlarge a size of a detail of the virtual map element or reduce the size of the detail of the virtual map element;
receive the following input information:
a field location via a selection at the virtual map element of the first interface;
a crop plant being grown at the field location by selection of the crop plant at the one or more interactive menus of the first interface;
a crop protection product used;
a number of applications of the crop protection product and amounts applied each time;
periods of time between the application(s) and harvesting time;
information relating to biomass of the crop plant that was present on each application of the crop protection product; and
environmental conditions during growing of the crop plant, especially on and/or after the application(s) of the crop protection product;
calculate an amount of a residue of the crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption at the harvesting time of the crop plant, using the input information;
wherein the amount of residue is calculated on the basis of a mathematical function relationship, wherein the mathematical function relationship describes degradation of the crop protection product as a function of time, wherein the mathematical function relationship has at least one parameter, wherein the at least one parameter is calculated with the aid of a machine learning model on the basis of one or more of the input information;
automatically update the calculated amount of residue of the crop protection product in response to a weather event at the crop plant and/or sensor data for the crop plant;
generate a second interface for display at the computer, the second interface displaying the calculated amount of residue relative to a target maximum amount of residue for the crop protection product; and
in response to a difference between the calculated amount of residue of the crop protection product and the target maximum amount of residue for the crop protection product being greater than a defined difference:
automatically identify an alternate crop protection product for the crop plant;
calculate an amount of a residue of the alternate crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption at the harvesting time of the crop plant; and
generate an updated second interface for display at the computer, the updated second interface displaying the amount of residue of the alternate crop protection product relative to a target maximum amount of residue for the alternate crop protection product.
2 . The device as claimed in claim 1 , wherein the mathematical function relationship is an exponential function, wherein the exponential function has two parameters, a starting value and a time constant, wherein the two parameters are calculated with aid of the machine learning model on the basis of one or more of the input information.
3 . The device as claimed in claim 2 , wherein the machine learning model has been trained in a monitored learning method using training data to learn a correlation between the one or more of the input information, preferably represented by a feature vector, and the at least one parameter of the mathematical function relationship.
4 . The device as claimed in claim 1 , wherein the at least one processor is configured to:
ascertain the target maximum amount of residue for the crop protection product in the crop plant or parts thereof;
compare the calculated amount of the residue with the target maximum amount ascertained; and
update the second interface to display whether and/or to what extent the calculated amount of the residue is above or below the maximum amount.
5 . The device as claimed in claim 1 , wherein the at least one processor is configured to:
identify countries and/or regions for which the calculated amount of the residue does not exceed any officially approved upper limit for the residue in the crop plant or parts thereof and/or identify traders for which the calculated amount of residue does not exceed any stipulated upper limit for the residue in the crop plant or parts thereof; and
update the second interface to display the countries and/or regions and/or traders that have been identified.
6 . The device as claimed in claim 1 , wherein the amount of the residue is displayed to a user as a proportion of a maximum amount stipulated by an official authority and/or a trader.
7 . The device of claim 1 , wherein the second interface further includes an indication of the crop plant being grown and the crop protection product used.
8 . A computer-implemented method comprising the steps of:
generating, by means of a computer system, a first interface for display at a computer that displays one or more interactive menus that allows user selection of at least a type of crop plant, wherein the interface includes a virtual map element to allow a user clicking on the virtual map element by means of finger movements to enlarge a size of a detail of the virtual map element or reduce the size of the detail of the virtual map element;
receiving and/or ascertaining input information by means of the computer system, wherein the input information includes:
a field location received and/or ascertained via a selection at the virtual map element of the first interface;
a crop plant being grown at the field location received and/or ascertained by selection of the crop plant at the one or more interactive menus of the first interface;
a crop protection product used;
a number of applications of the crop protection product and amounts applied each time;
periods of time between the application(s) and harvesting time;
information relating to biomass of the crop plant that was present on each application of the crop protection product; and
environmental conditions during growing of the crop plant, especially on and/or after the application(s) of the crop protection product;
calculating an amount of a residue of the crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption, preferably at the time of harvesting, by means of the computer system;
wherein the amount of residue is calculated on the basis of a mathematical function relationship, wherein the mathematical function relationship describes degradation of the crop protection product as a function of time, wherein the mathematical function relationship has at least one parameter, wherein the at least one parameter is calculated with the aid of a machine learning model on the basis of one or more of the input information;
generating a second interface for display at the computer, the second interface displaying the calculated amount of residue and a target maximum residue level for the crop protection product; and
in response to a difference between the calculated amount of residue of the crop protection product and the target maximum amount of residue for the crop protection product being greater than a defined difference:
automatically identifying an alternate crop protection product for the crop plant;
calculating an amount of a residue of the alternate crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption at the harvesting time of the crop plant; and
generating an updated second interface for display at the computer, the updated second interface displaying the amount of residue of the alternate crop protection product relative to a target maximum amount of residue for the alternate crop protection product.
9 . The method as claimed in claim 8 , wherein the mathematical function relationship is an exponential function, wherein the exponential function has two parameters, a starting value and a time constant, wherein the two parameters are calculated with aid of the machine learning model on the basis of one or more of the input information.
10 . The method as claimed in claim 9 , wherein the machine learning model has been trained in a monitored learning method using training data to learn a correlation between the one or more of the input information, preferably represented by a feature vector, and the at least one parameter of the mathematical function relationship.
11 . A system comprising:
a first computer system executed by a first processor;
a second computer system executed by a second processor;
wherein the first computer system is configured to generate a first interface for display at a computer that displays one or more interactive menus that allows user selection of at least a type of crop plant, wherein the interface includes a virtual map element to allow a user clicking on the virtual map element by means of finger movements to enlarge a size of a detail of the virtual map element or reduce the size of the detail of the virtual map element;
wherein the first computer system is configured to receive and/or ascertain the following input information:
a field location via a selection at the virtual map element of the first interface;
a crop plant being grown;
a crop protection product used at the field location by selection of the crop plant at the one or more interactive menus of the first interface;
a number of applications of the crop protection product and amounts applied each time;
periods of time between the application(s) and harvesting time;
wherein the first computer system is configured to transmit the input information via a network to the second computer system;
wherein the second computer system is configured to receive the input information via the network;
wherein the second computer system is configured to ascertain the following further input information if the further input information has not already been transmitted by the first computer system:
information relating to biomass of the crop plant that was present on each application of the crop protection product; and/or
environmental conditions during growing of the crop plant, especially on and/or after the application(s) of the crop protection product;
wherein the second computer system is configured to:
calculate an amount of a residue of the crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption, preferably at the time of harvesting, on the basis of the input information;
wherein the amount of residue is calculated on the basis of a mathematical function relationship, wherein the mathematical function relationship describes degradation of the crop protection product as a function of time, wherein the mathematical function relationship has at least one parameter, wherein the at least one parameter is calculated with the aid of a machine learning model on the basis of one or more of the input information; and
transmit the amount of the residue via the network to the first computer system; and
wherein the first computer system is configured to:
receive the amount of the residue via the network;
generate a second interface for display at the computer, the second interface the calculated amount of residue and a target maximum residue level for the crop protection product; and
in response to a difference between the calculated amount of residue of the crop protection product and the target maximum amount of residue for the crop protection product being greater than a defined difference:
automatically identify an alternate crop protection product for the crop plant;
calculate an amount of a residue of the alternate crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption at the harvesting time of the crop plant; and
generate an updated second interface for display at the computer, the updated second interface displaying the amount of residue of the alternate crop protection product relative to a target maximum amount of residue for the alternate crop protection product.
12 . The system of claim 11 , wherein the first computer system is configured to receive and/or ascertain said further input information and to transmit said further input information via the network to the second computer system.
13 . A computer program product comprising a non-transitory data carrier and program code which is stored on the data carrier and which triggers a computer system, in memory of which the program code has been loaded, to execute the following steps:
generating a first interface for display at a computer that displays one or more interactive menus that allows user selection of at least a type of crop plant, wherein the interface includes a virtual map element to allow a user clicking on the virtual map element by means of finger movements to enlarge a size of a detail of the virtual map element or reduce the size of the detail of the virtual map element;
receiving and/or transmitting the following input information:
a field location received via a selection at the virtual map element of the first interface;
a crop plant being grown at the field location received and/or ascertained by selection of the crop plant at the one or more interactive menus of the first interface;
a crop protection product used;
a number of applications of the crop protection product and amounts applied each time;
periods of time between the application(s) and harvesting time;
information relating to biomass of the crop plant that was present on each application of the crop protection product; and
environmental conditions during growing of the crop plant, especially on and/or after the application(s) of the crop protection product;
calculating an amount of a residue of the crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption, preferably at the time of harvesting of the crop plant, using the input information;
wherein the amount of residue is calculated on the basis of a mathematical function relationship, preferably based on an exponential function, wherein the mathematical function relationship describes degradation of the crop protection product as a function of time, wherein the mathematical function relationship has at least one parameter, wherein the at least one parameter is calculated with the aid of a machine learning model on the basis of one or more of the input information;
generating a second interface for display at the computer, the second interface displaying the calculated amount of residue and a target maximum residue level for the crop protection product; and
in response to a difference between the calculated amount of residue of the crop protection product and the target maximum amount of residue for the crop protection product being greater than a defined difference:
automatically identifying an alternate crop protection product for the crop plant;
calculating an amount of a residue of the alternate crop protection product in and/or on parts of the crop plant intended for human and/or animal consumption at the harvesting time of the crop plant; and
generating an updated second interface for display at the computer, the updated second interface displaying the amount of residue of the alternate crop protection product relative to a target maximum amount of residue for the alternate crop protection product.
14 . The computer program product as claimed in claim 13 , wherein the machine learning model has been trained in a monitored learning method using training data to learn a correlation between the one or more of the input information, preferably represented by a feature vector, and the at least one parameter of the mathematical function relationship.