Genetic Variability and Trait Identification for Enhanced Response to Drought Tolerance in Advanced Soybean Breeding Population
Charu Jamnotia
Department of Genetics & Plant Breeding, RVSKVV, Gwalior, India.
R. S. Sikarwar
Department of Genetics & Plant Breeding, RVSKVV, Gwalior, India.
Gyanesh Kumar Satpute *
Crop Improvement Section, ICAR-NSRI, Indore, India.
Giriraj Kumawat
Crop Improvement Section, ICAR-NSRI, Indore, India.
Falguni Bajpai
Department of Life Science, DAVV, Indore, India.
Santosh Kataria
Crop Improvement Section, ICAR-NSRI, Indore, India.
Prince Choyal
Crop Production Section, ICAR-NSRI, Indore, India.
Vangala Rajesh
Crop Improvement Section, ICAR-NSRI, Indore, India.
Sanjay Gupta
Crop Improvement Section, ICAR-NSRI, Indore, India.
Ramgopal Devdas
ICAR-NRC Orchids, Pakyong, Sikkim, India.
Milind Ratnaparkhe
Crop Improvement Section, ICAR-NSRI, Indore, India.
Rakesh Kumar Verma
Crop Production Section, ICAR-NSRI, Indore, India.
Sanjeev Kumar
Crop Protection Section, ICAR-NSRI, Indore, India.
*Author to whom correspondence should be addressed.
Abstract
Background: Soybean is a nutritionally important oilseed crop valued for its high protein content, nitrogen-fixing ability, and wide use in food, feed, and industry. Drought stress significantly reduces its yield, making genetic variability, heritability, and selection essential for developing high-yielding, drought-tolerant genotypes.
Aims: The present study was undertaken to assess the extent of variability and genetic parameters for yield and drought tolerance-related traits in an advanced breeding population of soybean under contrasting drought stress and non-stress environments, with emphasis on the comparison of performance during kharif 2023 and 2024.
Study Design: Randomized Block Design.
Place and Duration of Study: ICAR-National Soybean Research Institute, Indore, Summer and kharif between year 2023 and 2024.
Methodology: Analysis of variance was carried out to test the significance of differences among genotypes for various quantitative traits. Genetic parameters, including phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), broad-sense heritability and genetic advance as per cent of mean were estimated to understand the nature and magnitude of variability and the scope for selection.
Results: The analysis of variance revealed significant differences among genotypes for most of the characters in both years, indicating the presence of considerable genetic variability in the population. Mean plant height increased from 55.66 cm in 2023 to 61.54 cm in 2024, and the number of nodes per plant increased from 12.12 to 13.58. However, the number of pods per plant decreased from 42.51 in 2023 to 33.17 in 2024, pod weight per plant from 8.35 g to 6.92 g, and biomass per plant from 19.55 g to 17.77 g. PCV was higher than GCV for all traits in both years. High PCV and GCV were observed for seed weight per plant, pod weight per plant, number of pods per plant and biomass per plant. High GCV, heritability coupled with high genetic advance as per cent of the mean was recorded for number of pods per plant, pod weight per plant, seed weight per plant, number of branches /plant and canopy temperature depression in both years.
Conclusion: The study revealed substantial variability among the soybean genotypes. Traits showing high heritability and genetic advance may be effectively utilized for direct selection to improve yield and drought tolerance in soybean breeding programs.
Keywords: Soybean, advanced breeding population, year comparison, variability, heritability, genetic advance, drought stress