Genetic variability, correlation and path analysis for grain yield and component characters in greengram [Vigna radiata (L.) Wilczek]
Author(s):
Mohammed Saeed, RS Sain, AS Shekhawat, Jitendra Kumar Verma, LS Dhayal, SK Jain and OP Sharma
Abstract:
The current investigation involved in the assessment of 32 greengram genotypes, including a check, during the Kharif season of 2023. The study adopted a Randomized Block Design (RBD) with three replications and gathered data on 14 different traits to explore variability, heritability, genetic advancement, correlations, and path analysis. Regarding grain yield and its components, it was evident that RMG 975 performed exceptionally well, followed closely by RMG 492 and RMG 62. Upon closer examination of variability coefficients, it became apparent that Phenotypic Coefficient of Variation (PCV) exceeded Genotypic Coefficient of Variation (GCV), implying the influence of environmental factors on the expression of the studied traits. Notably, high GCV and PCV estimates were observed for grain yield per plant, number clusters per plant and number of pods per plant. Furthermore, the study found high heritability estimates for grain yield per hectare, straw yield per hectare, number of clusters per plant and grain yield per plant. In contrast, traits such as days to maturity, days to 50 % flowering and protein content showed low genetic advance as percentage mean estimates, suggesting their limited responsiveness to selective breeding. Grain yield per hectare showed significant and positive correlation with grain yield per plant followed by harvest index, number of clusters per plant and number of pods per plant whereas, days to 50% flowering showed positive but non-significant correlation and plant height, days to maturity showed negative and non-significant. Path analysis indicated that the straw yield per hectare had the highest positive direct effect on grain yield per hectare, followed by number of pods per plant and grain yield per plant. Cluster analysis revealed divergence in 32 accessions by making thirteen clusters. Cluster 7 and cluster 13 showed highest inter cluster distance signifying that hybridization between genotypes from these two clusters will exploit heterosis at a greater level. Consequently, these traits were recognized as efficient and promising targets for direct selection to enhance greengram productivity within the studied experimental materials.
How to cite this article:
Mohammed Saeed, RS Sain, AS Shekhawat, Jitendra Kumar Verma, LS Dhayal, SK Jain, OP Sharma. Genetic variability, correlation and path analysis for grain yield and component characters in greengram [Vigna radiata (L.) Wilczek]. Pharma Innovation 2024;13(12):110-115.