The relevance of this research lies in the need to identify the specific features of productivity formation in sunflower hybrids and to establish the relationship between dry matter accumulation at different growth stages and crop yield under varying nutritional conditions. This study aimed to examine the impact of nutritional regimes on the growth, development, and productivity formation of sunflower hybrid agrocenoses, with the application of mineral fertilisers and the growth regulator Kvadrostym, under specific soil and climatic conditions. The research employed both theoretical (statistical analysis) and practical (descriptive and comparative) methods. The following indicators were assessed: dry matter content in plant samples at defined stages of sunflower hybrid development, yield levels, and the interrelationship between these parameters. It was found that as sunflower plants progressed through their growth stages, dry matter accumulation increased accordingly. The values differed depending on the developmental characteristics of the hybrids under study. The highest values were recorded at the BBCH 74-77 growth stage. The indicators varied according to the hybrid and nutritional conditions, ranging from 6.12 to 8.62 t/ha. The highest dry matter accumulation was observed in crops of the hybrid ES Monalisa. The application of the growth regulator Kvadrostym contributed to increased dry matter accumulation and, consequently, to higher yields across all sunflower hybrids. The research results demonstrated a consistent relationship between dry matter accumulation in sunflower plants and crop yield at all stages of development. Analysis of linear regression models indicated a strong correlation between these parameters. At the BBCH 74-77 stage, the coefficient of determination varied by sunflower hybrid from 0.9829 to 0.9934. The findings support conclusions regarding the rational use of mineral fertilisers and growth-regulating products to create optimal nutritional conditions for sunflower hybrids
Helianthus annuus; weather conditions; regression model; dry matter; fertilisers; yield