1Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda-210 001, Uttar Pradesh, India
2Department of Agronomy, Banda University of Agriculture and Technology, Banda-210 001, Uttar Pradesh, India
*Corresponding Author: Hitesh Kumar, Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda-210 001, Uttar Pradesh, India, Email: hiteshkmr25@gmail.com
Online published on 22 July, 2025.
Chickpea is grown on a large scale in India but the productivity is very low as compared to other chickpea-growing countries. Because, in India, the crop is affected by many biotic and abiotic stresses and also has a narrow genetic base in germplasm lines, which are the prerequisite of any breeding program for developing high-yield varieties. The breeding program’s success depends on genetic variation and efficient selection strategies that make it possible to exploit existing genetic resources.
The agro-morphological characterization of 94 chickpea germplasm accessions including four checks viz., JG 14, JG 16, JAKI 9218 and Radhey was carried out during Rabi 2018-19. The experiment was laid out in augmented design in nine blocks. The analysis of variance was estimated with the help of statistical software SPAD and using the statistical package Windostat version 9.1.
The significant variance among the germplasm lines was found for most of the studied traits. Genetic diversity analysis revealed the grouping of genotypes into eight distinct clusters irrespective of breeding centers. The maximum number of 32 genotypes was fallen in cluster II and the minimum in cluster VI which consisted of 8 genotypes, whereas clusters IV and VIII were identified as bi-genotypic clusters. Clusters VII and IV showed maximum inter-cluster distance indicating the maximum genetic diversity among the genotypes of these clusters. Principal component analysis transformed data into three variables (PCs) which contributes 97.78 percent of the total variation. The genotypes identified in this study will be utilized in chickpea improvement programs.
Agro-morphological traits, Cluster analysis, D2-Statistics, Principal component