Program code and methodology for cluster analysis of data from the information and technical system of precision agriculture to identify areas of heterogeneity in the agrobiological state of agricultural land biodiversity
Year: 2025
Type: article
Abstract: Ukraine has one of the highest fertility rates in the world. Therefore, to ensure maximum yields when growing crops, an important component is constant monitoring of the agrobiological state during the entire period of growing crops, before sowing and after harvesting. This makes it possible to optimize the rates of application of technological materials and, accordingly, mini-mize the costs of growing crops. The implementation of constant monitoring of the agrobiolog-ical state of agricultural lands is an important element of modern agricultural production and is possible using a wide range of devices of information and technical systems for monitoring the agrobiological state of agricultural lands, ground, air, and space-based at different stages of growing crops. As a result, we have large data sets that require their prompt processing, visuali-zation, presentation for working with them, and making operational decisions for effective management of technological operations. That is why, to work with large data sets, a method of cluster analysis of data from the information and technical system of precision agriculture of the agrobiological state of the biodiversity of agricultural lands has been developed. The pro-posed program code allows for the differentiated application of technological material (seeds, fertilizers, plant protection products, etc.) based on monitoring data using information and technical systems for operational monitoring of the agrobiological state of agricultural lands. According to preliminary calculations, possession of such information will allow for saving technological material by 10–25 % and help to increase the yield of agricultural crops by 10–20 centners per hectare.
Authors: O.O. Brovarets, O.Yu. Sapelnikova
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDGs: Zero hunger, Life on land
Open Access status: bronze
OpenAlex ID: W4411419932