The article presented the results of a two-year field experiment investigating the influence of varietal characteristics, agrotechnological practices, and weather conditions on soybean yield using predictive modelling. The relevance of the study stems from the need to improve the stability of soya bean yields in the context of climate change and the importance of using biological plant protection products (biofungicides). The aim was to establish the effectiveness of various pre-sowing seed treatment schemes and foliar application of fungicides and micronutrients, as well as to develop mathematical models for predicting soyabean yield depending on weather conditions. Field studies were conducted in 2024-2025 at the Training and Production Centre of Bila Tserkva National Agrarian University using soybean varieties ‘RGT Salsa’ and ‘RGT Saidina’. The experiment included 50 variants. It was established that the highest average yield (2.71 t/ha) was obtained for the variety ‘RGT Saidina’ under the combined use of the fungicides Maxim XL, Apron XL, the inoculant BioMAG Soya, and double application of the fungicide Kolosal Pro with micronutrient fertilisers Intermag Molybdenum and Quantum Bor Active at the budding stage (BBCH 51-59) and the flowering stage (BBCH 60-69). Under this scheme, variants with the biofungicide Fitosporin-M Soya provided a yield of 2.65 t/ha, confirming the high effectiveness of biological protection. Mathematical modelling revealed a high level of agreement between actual and calculated data (error up to 0.07 t/ha). Cluster analysis of the 50 studied variants based on soybean grain yield identified three main groups according to productivity level. The first cluster included variants with yields above 2.5 t/ha, most of which combined the use of the inoculant BioMAG Soya with the fungicides Maxim XL (1.0 L/t) + Apron XL (0.5 L/t), as well as the fungicide Kolosal Pro and micronutrient fertilisers Intermag Molybdenum (1.0 L/ha) + Quantum Bor Active. The practical value of the results lies in identifying optimal combinations of biological and chemical fungicides, inoculants, and micronutrient fertilisers to increase soybean productivity, as well as in the possibility of forecasting yield based on climatic indicators
LABUNSKYI et al. (Mon,) studied this question.