Principal component and genetic diversity analysis for morpho-biochemical traits in cluster bean (Cyamopsis tetragonoloba L.)

Abstract

Precise selection of superior genotypes for yield and its attributing traits is of utmost importance for a successful breeding program, but the complex nature of yield makes this selection difficult. The present study was conducted at dry land research area, CCSHAU, Hisar, Haryana, India, during Kharif 2022 to measure the genetic diversity among the cluster bean genotypes and to select the diverse parents for recombination breeding. Data were recorded on 17 quantitative traits using 50 cluster bean genotypes. D2 analysis distributed all the genotypes into five clusters. Cluster IV had the maximum intra-cluster distance. The crossing among the genotypes of clusters I and III, III and IV, and I and IV would result in novel recombinants, as they showed high inter-cluster distance. In the PCA study, the first five principal components (PCs) had eigenvalues greater than one, and they cumulatively explained 83.29% of the total variation present in the original dataset. The first principal component (PC 1) explained 37.87%, while PC 2, PC 3, PC 4, and PC 5 explained 18.04, 12.90, 8.23, and 6.25% of the total variability, respectively. PC 1 has captured maximum variability for seed yield and its attributing traits, along with gum content. The genotypes, RGr 20-15, X 25, RGr 18-1, HG 884, RGr 20-7, HG 2-20, HG 19-4, HG 563, GD 567, and GG 1806, were the top-ranking genotypes upon PC analysis with high positive PC 1 scores.