Assessing genetic variability and identifying stable soybean genotypes across rainfed and irrigated planting conditions using multi-trait stability index (MTSI)

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Monika Soni
Manoj Kumar Shrivastava
Pawan K. Amrate
Stuti Sharma
Yogendra Singh
Vikrant Khare

Abstract

Soybean's constrained genetic diversity renders it particularly vulnerable to environmental influences. However, genetic variability and stability across diverse planting conditions are essential prerequisites for effective soybean breeding programs. The aim of this study was to assess genetic variability and identify stable-performing soybean genotypes suitable for both rainfed and irrigated planting conditions of central India, with the goal of enhancing soybean breeding efforts. Advanced soybean breeding lines were evaluated under rainfed and irrigated conditions using a randomized complete block design. Phenotypic assessments were conducted to analyse genetic variability, associations, direct and indirect effects, employing multiple regression analysis and determining multi-trait stability index (MTSI). Phenotypic coefficient of variation (PCV) exceeded genotypic coefficient of variation (GCV) for all the traits across all the environments. The high heritability (h2) was combined with substantial genetic advance, for pods per plant, seeds per plant, seed weight, biological yield, and seed yield. Correlation and regression analyses revealed consistent positive associations of biological yield and harvest index with seed yield under both the planting condition. Path analysis identified biological yield as having the highest direct effect on seed yield in rainfed and irrigated planting conditions. MTSI identified JS 22-101is the most stable and superior genotypes for rainfed and irrigated planting conditions of central India. Biological yield emerged as the primary yield-contributing trait identified through holistic approaches employed in this study. Across all traits examined JS 22-101 demonstrated stability in both rainfed and irrigated planting conditions. This study underscores the importance of refining selection criteria for optimizing soybean breeding programs, contributing to agricultural genetic enhancement.

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How to Cite
Monika Soni, Manoj Kumar Shrivastava, Pawan K. Amrate, Stuti Sharma, Yogendra Singh, & Vikrant Khare. (2024). Assessing genetic variability and identifying stable soybean genotypes across rainfed and irrigated planting conditions using multi-trait stability index (MTSI). INDIAN JOURNAL OF GENETICS AND PLANT BREEDING, 84(03), 374–384. https://doi.org/10.31742/ISGPB.84.3.8
Section
Research Article