Genetic studies for detection of most diverse and high yielding genotypes among chickpea (CICER arientinum l.) germplasm

Genetic variation occurring naturally in germplasm is highly valuable resource of alleles that can be deployed for genetic improvement of a species. Screening of available genetic stock for detection of most diverse and high yielding genotypes is a pre requisite for a successful crop breeding program. For this purpose, a research experiment comprising of sixty-eight elite chickpea germplasm genotypes along with two commercial varieties were sown under tri-replicate randomized complete block design during the winter season of 2020-21. D2 statistics, principle component analysis and cluster analysis were employed to detect the most genetically variable and high yielding chickpea genotypes. D2 statistics extracted higher values for standard deviation and coefficient of variation indicating that the studied genotypes possess considerable amount of genetic variation in performance of studied different traits. Principle component analysis distinguished the traits into eight components. Results revealed that PC1 and 2 extracted >1 Eigen values explaining that these components have major contribution in genetic variability. Cluster analysis distributed the genotypes into four distinguished clusters. Agglomerative dendrogram of genotypes was constructed by Ward's method. On the basis of Euclidean distance it was observed that members of cluster 3 (G.P-110, G.P-111, G.P-115, G.P-116, G.P-121, G.P-125, G.P-138, G.P-139, G.P-150, G.P-151, G.P-164, G.P-165) and cluster 4 (G.P-112, G.P-126, G.P-140, G.P-152, G.P-166) were most diverse. Results also showed that the genotypes of cluster 3 were high yielding and genetically diverse as well. Therefore, they may be preferred while making selections for chickpea genetic improvement program. (author)