Delineation of Genetic Diversity in Chickpea Employing Multivariate Techniques
Shivakant Singh Rajpoot
Department of Genetics & Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, 474002, India.
M.K. Tripathi *
Department of Genetics & Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, 474002, India and Zonal Agricultural Research Station, Morena, 476001, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, India.
Riya Mishra
Department of Genetics & Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, 474002, India.
D. K. Payasi
RAK College of Agriculture, Sehore, Rajmata Vijayaraje Scindia Agricultural University, Gwalior, Madhya Pradesh, India.
Ankit Pandey
KNK-College of Horticulture, Mandsaur, 458001, Rajmata Vijayaraje Scindia Agricultural University, Gwalior, Madhya Pradesh, India.
Swati Singh Tomar
Zonal Agricultural Research Station, Morena, 476001, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, India.
Sanjeev Sharma
Department of Genetics & Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, 474002, India.
Jagendra Singh
Department of Genetics & Plant Breeding, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, 474002, India and Zonal Agricultural Research Station, Morena, 476001, Rajmata Vijayaraje Scindia Agriculture University, Gwalior, Madhya Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
Chickpea (Cicer arietinum L.) is a vital legume crop valued for its nutritional richness and ability to improve soil fertility. Despite its significance, productivity is constrained by a narrow genetic base and susceptibility to multiple stresses. In this study, 69 diverse chickpea genotypes were evaluated during the Rabi 2022-23 at RVSKVV, Gwalior to assess genetic variability, interrelationships among traits and genetic divergence using multivariate analysis for 12 quantitative traits. Significant genotypic differences were observed for all the traits. Yield per plant exhibited the highest GCV (25.20%) and PCV (25.43%) coupled with high heritability (98.10%) and genetic advance (51.42%) indicating strong additive gene effects and potential for improvement via selection. Correlation studies revealed that seed yield was positively associated with harvest index, biological yield and number of primary branches, while negatively corelated with plant height. Furthermore, path coefficient analysis underscored harvest index and biological yield as major direct contributors to seed yield at both genotypic and phenotypic levels, suggesting these as reliable selection criteria. Mahalanobis D² analysis grouped the genotypes into 10 clusters, with maximum inter-cluster distance between clusters VIII and X (24.76), highlighting opportunities for exploiting heterosis through crosses between genetically divergent parents. Traits like harvest index (38.01%) and biological yield (25.55%) contributed most to total divergence. Cluster III exhibited the highest mean seed yield, while cluster X was found superior for harvest index and branching traits. The findings emphasized the existence of considerable genetic variability in the genotypes investigated such as SAGL-152237, SAGL-162376, RVSSG-85, SAGL-152250, RVSSG-75, SAGL-152231 along with genetically variable entries from clusters VII and V, offering valuable insights for utilizing in breeding programmes aimed to develop high-yielding, stress-resilient chickpea cultivar (s) through strategic parent selection and hybridization.
Keywords: Chickpea (Cicer arietinum L.), correlation analysis, genetic advance, genetic variability, heritability, mahalanobis d² statistics, path coefficient