Multivariate Characterization and Genetic Diversity Assessment of Winged Bean [Psophocarpus tetragonolobus (L.) DC.] Germplasm for Genetic Improvement
Ankit Kumar Verma
Department of Vegetable Science, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya-224 229, U.P., India.
Aastik Jha *
Department of Vegetable Science, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya-224 229, U.P., India.
Anshuman Mishra
Department of Vegetable Science, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya-224 229, U.P., India.
*Author to whom correspondence should be addressed.
Abstract
Assessment of genetic diversity is essential for the effective utilisation of winged bean [Psophocarpus tetragonolobus (L.) DC.] germplasm in breeding programmes. The present study evaluated 28 winged bean genotypes, comprising 27 advanced breeding lines and one check variety, in a Completely Randomised Block Design with three replications to investigate genetic variability, divergence and trait relationships using multivariate statistical approaches. Analysis of variance revealed highly significant (P ≤ 0.01) differences among genotypes for all nineteen quantitative and quality traits, indicating the existence of substantial genetic variability. Mahalanobis D² analysis grouped the genotypes into four distinct clusters, with Cluster III containing the maximum number of genotypes (11), while Cluster IV consisted solely of genotype NDWB-22-14. The highest inter-cluster distance was observed between Clusters II and IV (14.203), suggesting their suitability for hybridisation to generate broad genetic variability. Cluster IV recorded superior mean performance for major yield attributes, including pod length (28.33 cm), number of pods per plant (50.25), green pod yield (167.74 q ha⁻¹) and seed yield (49.54 q ha⁻¹). Green pod yield per hectare contributed the highest proportion (7.72%) towards total genetic divergence. Principal component analysis identified six principal components with eigenvalues >1, accounting for 86.78% of the total variation. The first principal component (44.79%) was primarily associated with seed yield, green pod yield, number of pods per plant and pod length, whereas the second component (14.41%) differentiated genotypes based on vegetative and quality traits. The PCA biplot further identified NDWB-22-01, NDWB-22-02, NDWB-22-08, NDWB-22-09, NDWB-22-12, NDWB-22-13 and the check variety Kashi Annapurna as promising high-yielding genotypes. Overall, the combined D² and PCA analyses identified genetically divergent and superior genotypes that can serve as valuable parental resources for winged bean improvement programmes.
Keywords: Genetic diversity, Mahalanobis' D², Principal component analysis, Multivariate analysis, Winged bean, Parental selection