Evaluation of Genetic Diversity through D2 Statistic in Chickpea (Cicer arietinum L.)

Abstract

The present investigation was conducted at the Agriculture Research Farm, Department of  Genetics and Plant Breeding, College of Agriculture, Rajmata Vijyaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, Madhya Pradesh, India. The objective of the investigation was to assess the genetic diversity among 71 different chickpea genotypes in relation to their yield and its attributing traits. The experimental design employed was a complete randomized block design with two replications. A comprehensive set of observations was made on twelve distinct yield accrediting traits from five randomly selected plants within each genotype. Based on D2 Statistics analysis, the 71 chickpea genotypes were classified into 26 distinct clusters. Conspicuously, the cluster with the highest numbers of genotypes was designated as cluster 1. A remarkable finding emerged from the analysis of intra-cluster distances, with cluster 16 displaying the greatest distance within its constituents. The evaluation of inter-cluster distances revealed significant dissimilarity between clusters 22 and 26, suggesting presence of considerable genetic variation between these clusters. Conversely, the inter-cluster distance was minimal between clusters 2 and 4, indicating a closer genetic relationship between genotypes ICCV 201109 and SAGL- 162387. In terms of the genetic diversity analysis, it became evident that the yield related traits exerting the most substantial influence on the overall genetic divergence among the 71 chickpea genotypes were biological yield per plant, 100-seed weight, and the numbers of pods per plant. In contrast, the numbers of effective pods per plant contributed minimally to the overall genetic divergence. Based on the findings from both inter-cluster distances and individual performance assessments (per se performance), two specific genotypes viz., ICCV 201207 and SAGL 22-121, were short out as promising for inclusion in a hybridization programme. These findings contribute to a deeper understanding of chickpea genetic variability and lay the groundwork for further breeding programmes aimed to enhance chickpea crop productivity.