INFORMATION AND INSTRUMENTAL SUPPORT OF SITE-SPECIFIC MANAGEMENT FOR AGROCHEMICALS
Rubrics: AGRICULTURAL ECONOMICS AND POLICIES
Authors:
1.
St. Petersburg State University
2.
St. Petersburg State University
Type:
Article
eLocation:
Status:
Published
Received:
06.12.2022
Accepted:
15.12.2022
Published:
25.12.2022
Language:
Russian
Keywords:
tochnoe zemledelie, differencirovannye tehnologii, bespilotnaya aviacionnaya sistema, sistema parallel'nogo vozhdeniya, ortofotoplan, zernovye
Abstract (English):
Precision farming technologies can significantly improve the production quality and volume, while reducing the negative impact on the environment. This is achieved through the application of optimal agrochemicals doses in each elementary field zone through the joint use of remote sensing data, agrochemical, weather data, etc., as well as through the modernization of agricultural machinery (the use of an on-board computer, sensors, parallel driving systems, etc.). The aim of the study was to develop a set of approaches for information and instrumental support of site-specific management using native ready-made solutions, as well as open libraries and programs. The object of the study are two experimental agricultural fields, which are part of the Agrophysical Institute biopolygon (growing crops - cereals). Experiments have been carried out since 2019 using the native unmanned aerial system Geoscan-401. The result of the information support of agricultural technology is a specialized task map, which is loaded into the on-board computer of agricultural machinery for the subsequent application of a certain nitrogen dose in each elementary zone. The map is built on the basis of the allocation of homogeneous technological zones by methods of controlled classification. At the final stage of the implementation of the proposed approach, an important component is the parallel driving system, which allows the most efficient coverage of the territory (without passes, without entering the same zone twice). AgOpenGPS open technology with free software was chosen as the basis for creating a prototype of an analog parallel driving system. Since 2019, more than 20,000 source images have been collected and processed for the presented experimental agricultural fields. As a result, more than 20 multilayer orthophotomaps were generated to apply machine learning methods to identify homogeneous technological zones. The proposed approach for information support of differentiated technologies has been worked out, and a prototype of the native analogue of the parallel driving system has been implemented and tested.
Precision farming technologies can significantly improve the production quality and volume, while reducing the negative impact on the environment. This is achieved through the application of optimal agrochemicals doses in each elementary field zone through the joint use of remote sensing data, agrochemical, weather data, etc., as well as through the modernization of agricultural machinery (the use of an on-board computer, sensors, parallel driving systems, etc.). The aim of the study was to develop a set of approaches for information and instrumental support of site-specific management using native ready-made solutions, as well as open libraries and programs. The object of the study are two experimental agricultural fields, which are part of the Agrophysical Institute biopolygon (growing crops - cereals). Experiments have been carried out since 2019 using the native unmanned aerial system Geoscan-401. The result of the information support of agricultural technology is a specialized task map, which is loaded into the on-board computer of agricultural machinery for the subsequent application of a certain nitrogen dose in each elementary zone. The map is built on the basis of the allocation of homogeneous technological zones by methods of controlled classification. At the final stage of the implementation of the proposed approach, an important component is the parallel driving system, which allows the most efficient coverage of the territory (without passes, without entering the same zone twice). AgOpenGPS open technology with free software was chosen as the basis for creating a prototype of an analog parallel driving system. Since 2019, more than 20,000 source images have been collected and processed for the presented experimental agricultural fields. As a result, more than 20 multilayer orthophotomaps were generated to apply machine learning methods to identify homogeneous technological zones. The proposed approach for information support of differentiated technologies has been worked out, and a prototype of the native analogue of the parallel driving system has been implemented and tested.
Keywords:
tochnoe zemledelie, differencirovannye tehnologii, bespilotnaya aviacionnaya sistema, sistema parallel'nogo vozhdeniya, ortofotoplan, zernovye
tochnoe zemledelie, differencirovannye tehnologii, bespilotnaya aviacionnaya sistema, sistema parallel'nogo vozhdeniya, ortofotoplan, zernovye
