Rushikesh Dhokade, Priyanka Gupta, Shalini Pathak, Akash Barela and Venkatesh Charke
Abstract
The study aimed to identify productive selection criteria for genetic enhancement in lentils. An experiment involving 50 lentil genotypes with 4 check variety (IPL-526, IPL-329, IPL-315, IPL-225) was conducted to evaluate 13 quantitative traits in augmented design during the rabi season, 2023-24. This study focused on genetic diversity parameters and principal component analysis (PCA). Data were collected for the following traits: days to flowering initiation, days to 50% flowering, days to maturity, primary branches per plant, secondary branches per plant, chlorophyll content (mg/m2), pods per plant, plant height (cm), seed index (g), number of seeds per plant, biological yield per plant, harvest index (%) and seed yield (g). The collected data was analyzed using K-means clustering and PCA. Analysis of variance indicated significant variation among the genotypes for all measured traits. K-means clustering grouped the 54 genotypes into 10 clusters, with clusters II and VIII showing the highest inter-cluster distance (115.748), indicating substantial genetic diversity between the genotypes. PCA identified 13 principal components (PCs), with the first five components having eigen value greater than 1, collectively accounting for 80% of the genetic variation. PCI highlighted genotypes with high yield-contributing traits, including EC-542206, ILL-9979, ILL9970, L-556, BR-2, EC542161, EC208355, ILL7928, and BAM-6. These diverse genotypes can be used directly in hybridization programs.