Research Articles
Vol. 12 No. 2 (2025)
Unravelling soybean yield potential: Exploring trait synergy, impact pathways, multidimensional patterns and biochemical insights
Department of Genetics and Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior 474 002, India
Department of Genetics and Plant Breeding , Jawaharlal Nehru Agriculture University, Jabalpur 482 004, India
Department of Genetics and Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior 474 002, India
Department of Genetics and Plant Breeding , Jawaharlal Nehru Agriculture University, Jabalpur 482 004, India
Department of Genetics and Plant Breeding , Jawaharlal Nehru Agriculture University, Jabalpur 482 004, India
Department of Genetics and Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior 474 002, India
Department of Genetics and Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior 474 002, India
Department of Genetics and Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior 474 002, India
Abstract
As the major oilseed Kharif crop, soybean (Glycine max L. Merill) requires continuous improvement to compete with changing climatic conditions. For this purpose, research was conducted during the Kharif 2022, at AICRP Soybean Seed Breeding Farm, JNKVV, Jabalpur, focusing on soybean genetics, yield related traits and their implications for enhancing global food security. A total of 118 genotypes, comprising 115 Recombinant Inbred Lines (RILs) with three checks were meticulously analyzed. The study encompassed a comprehensive evaluation, employing correlation coefficient analysis, path coefficient analysis and principal component analysis. Ten critical yield- related traits were systematically recorded, including flowering patterns, branching architecture, plant height and seed yield. Notably, strong positive correlations were found between seed yield and harvest index, 100-seed weight, number of seeds per plant and biological yield. Path analysis unveiled these traits' direct and indirect effects on seed yield, with harvest index and biological yield as key contributors. Principal Component Analysis (PCA) successfully condensed this data into seven principal components, explaining 95.93 % of the variance, with Principal Component 1 (PC1) bearing the highest impact. PC1 incorporated traits critical for soybean improvement, including seed yield and 100-seed weight. Furthermore, biochemical analysis of 31 RILs and 2 checks revealed moisture content ranging from 3 to 6 %, fat content 16-21 %, proteins 34-42 % and ash ranged from 4-6 %. This research offers valuable insights into soybean genetics and trait interactions, providing a foundation for future breeding programs aimed at enhancing global food security in an ever-changing world.
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