Mapping Genetic Diversity in Green Gram: A Multivariate Approach for Coastal Adaptability
D. R. Pani *
ICAR-National Bureau of Plant Genetic Resources, Base Centre, Cuttack, Odisha, India.
S. Satpathy
Bhadrak Autonomous College, Bhadrak, Odisha, India.
L. K. Bose
ICAR-Central Rice Research Institute, Cuttack, Odisha, India.
N. N. Jambhulkar
ICAR-Central Rice Research Institute, Cuttack, Odisha, India.
*Author to whom correspondence should be addressed.
Abstract
Green gram [Vigna radiata (L.) Wilczek] is widely cultivated and consumed throughout India. But There is a pressing need for intensified interventions to enhance both the production and productivity of pulses in general, and green gram in particular. This study aims to estimate heritability and genetic advance, classify germplasm into distinct groups based on genetic variability, evaluate the associations between grain yield and its component traits, and identify diverse genotypes with desirable characteristics for use in hybridisation programmes aimed at developing improved recombinants. In the present paper, an assessment of genetic divergence in a set of 41 accessions of green gram was used following standard statistical procedure and a multivariate analysis approach. The field experiments were carried out in a randomised block design with three replications during the rabi season of 2016-2018. The study revealed significant differences among the genotypes for all the traits. The highest genotypic coefficient of variation (GCV) was observed for seed yield per plant (34.28), followed by the number of clusters per plant (23.76), number of branches per plant (16.11), 100-seed weight (15.87), and plant height (15.75). These results indicate substantial genetic variability, suggesting considerable potential for improvement of these traits through selective breeding. Seed yield had a maximum phenotypic and genotypic coefficient of variation and was grouped into thirteen clusters, with the highest number of 18 genotypes in cluster-I, seven in cluster-III, five in cluster-V, two in cluster-X and one genotype each in rest nine clusters. Yield ha-1 contributed maximum (21.4 per cent) towards divergence, followed by plant height (15.2%) and pods/plant (14.7%). Average intra- and inter-cluster D2 values revealed no intra-cluster distance between clusters II, IV, VI to IX and XI to XIII being monogenic in nature. Based on genetic divergence studies, the genotypes, viz. IC-565245 (Cluster-IX) and IC-568946 (Cluster-XII), having the highest inter-cluster distance is recommended to be used as parents for the green gram hybridisation programme to obtain better transgressive segregants. Further, the traits like seed yield, number of branches/plant and number of clusters/plants with high heritability estimates (in a broad sense) along with high genetic advance as a percentage of mean would be more effective for further improvement of yield and yield components. The present investigation revealed that the genotypes studied are very diverse and can be useful for selective breeding of specific traits and in enhancing the genetic base of breeding programs in future.
Keywords: Genetic divergence, green gram, heritability, quantitative traits