Vol. 12, Issue 10 (2023)

Author(s):
Chinta Revathi and Gaibriyal M Lal

Abstract:
The current investigation involved in the assessment of 20 Greengram genotypes, including a check, during the kharif season of 2022. The study adopted a Randomized Block Design (RBD) with three replications and gathered data on 13 different traits to explore variability, heritability, genetic advancement, correlations, and path analysis.Analysis of variance revealed that the germplasm exhibited significant genetic variability for most of the assessed traits. Regarding grain yield and its components, it was evident that LGG-450 performed exceptionally well, followed closely by VBN-3 and AMULYA. 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 to moderate GCV and PCV estimates were observed for clusters per plant, biological yield, and economic yield. Furthermore, the study found high heritability estimates for clusters per plant, economic yield, biological yield, and pods per plant. In contrast, traits such as days to 50% pod setting, days to maturity, and days to 50% flowering showed low genetic advance estimates, suggesting their limited responsiveness to selective breeding. The correlation analysis revealed significant positive associations between grain yield per plant and various other traits, including plant height, primary branches per plant, clusters per plant, pods per plant, biological yield, and seed index. Additionally, path analysis, conducted at both phenotypic and genotypic levels. It is identified that plant height, biological yield, harvest index, and seed index are directly influenced on yield. Consequently, these traits were recognized as efficient and promising targets for direct selection to enhance Greengram productivity within the study's experimental materials.