Classification of black gram [Vigna mungo (L.) Hepper] germplasm based on the genetic differences for yield attributing traits

Fifty black gram genotypes were evaluated to identify potential genotypes based on their spatial distances. Principal component analysis (PCA) revealed that first two PC’s recorded more than one eigen value and explained 57.2% of total variation. The principal components PC I and PC II contributed 38.2%, and 19.02%, respectively. The first five components cumulatively explained 82.390% of variation towards total variability. The first principal component (PC-I) contributed maximum by grain yield plant−1, number of pods plant−1, test weight, number of seeds pod−1, pod length and number of branches plant−1. PC-II had maximum variation for days to 50% flowering, days to maturity and plant height. The genotypes were distributed into eight different clusters, while traits got clumped in to two groups in two dimensional (2D) scatter plots. The traits including number of branches plant−1, number of clusters plant−1, number of pods plant−1, number of seeds pod−1, test weight and grain yield plant−1 in first group; days to 50% flowering, days to maturity and plant height under second group were positively correlated among themselves. The traits grain yield plant−1, number of pods plant−1, number of clusters plant−1, test weight, number of branches plant−1, pod length and number of seeds pod−1 had longer vector lengths indicating higher discriminating power in evaluating germplasm. While, the agglomerative hierarchial cluster analysis of genotypes resulted in nine clusters. The clustering pattern in both clustering methods was overlapping for majority of genotypes. The genotypes viz., LBG 932, LBG 787, VBN 11, VBN 8, DKU 87, TBG 141 and GBG 12 were grouped into different clusters in both the methods and can be used in hybridization programmes for isolating transgressive segregants. © The Author(s) under exclusive licence to Society for Plant Research 2023.