Seed heterogeneity, fractional composition and thousand seed weight of soybean depending on varietal composition - Kravchenko, V.; Poltoretska, N.; Kononenko, L.; Vyshnevska, L.; Klymovych, N. (Scientific Progress & Innovations, 2025)
The article presents the results of a field study conducted under the agro-climatic conditions of the Uman district, Cherkasy region, aimed at assessing seed heterogeneity, fractional composition, and thousand-seed weight of soybean depending on varietal composition. The study included five soybean varieties: ES Mentor, Halleck, OAC Brook, OAC Strive, and OAC Lakeview. Fractional composition was determined by dividing seeds into large (>6.5 mm), medium (5.0–6.5 mm), and small (<5.0 mm) fractions using the sieving method. Thousand-seed weight was determined according to standard procedures, and protein content was measured using near-infrared spectroscopy (NIRS). The results revealed pronounced varietal differences. ES Mentor and OAC Lakeview were characterized by a predominance of the large seed fraction (>6.5 mm) exceeding 55 %, which indicates their suitability for large-seeded soybean production. Halleck and OAC Strive demonstrated a more uniform distribution of seeds across fractions, making them versatile for various uses. OAC Brook had the lowest proportion of large seeds (>6.5 mm) and the highest proportion of small ones (<5.0 mm), up to 28 %, indicating its distinct morphometric differentiation. The thousand-seed weight ranged from 131.2 g in OAC Brook to 168.4 g in ES Mentor, reflecting a significant influence of genetic factors. Protein content varied from 36.5 % in ES Mentor to 40.8 % in OAC Brook, confirming an inverse relationship between seed weight and protein accumulation. Additionally, significant correlations were established between thousand-seed weight, protein content, and fractional composition, allowing prediction of seed quality traits based on varietal characteristics. Thus, it was determined that the qualitative and biochemical characteristics of soybean seeds are largely defined by varietal features, and the obtained results can be applied to optimize breeding programs and cultivation technologies.