Legume Research
Web of Science
  • Year: 2026
  • Volume: 49
  • Issue: 6

Multivariate Genetic Diversity Assessment in Chickpea (Cicer arietinum L.) Genotypes under Different Environmental Conditions

  • Author:
  • Abhinav Yadav1, Shiva Nath1, Vinay Kumar Chourasiya2, Jutika Boro3,*, Dharmendra Kumar1, Banoth Srikanth1, Deeksha Bharti4
  • Total Page Count: 7
  • Page Number: 967 to 973

1Department of Genetics and Plant Breeding, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya-224 229, Uttar Pradesh, India

2Department of Seed Science and Technology, Acharya Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya-224 229, Uttar Pradesh, India

3CSIR- National Botanical Research Institute, Lucknow-226 001, Uttar Pradesh, India

4Department of Genetics and Plant Breeding, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj-211 007, Uttar Pradesh, India

*Corresponding Author: Jutika Boro, CSIR- National Botanical Research Institute, Lucknow-226 001, Uttar Pradesh, India, Email: jutikaboronbri@gmail.com

Abstract

This research assesses the genetic diversity among 55 chickpea genotypes, comprising both parental lines and F1 hybrids, through D2 analysis in conditions of both timely sown (TS) and late sown (LS). Conducted at the Genetics and Plant Breeding Research Farm, Acharya Narendra Deva University of Agriculture and Technology, Ayodhya, during the Rabi seasons of 2021-22 and 2022-23.

The experiment was laid out in a randomized block design (RBD) with three replications. Data was collected on eleven agronomic traits. Statistical analyses, including D2 statistics, cluster analysis and principal component analysis (PCA), were conducted to assess the genetic diversity among the chickpea genotypes.

Both TS and LS conditions revealed six clusters. In TS condition, the majority genotypes were found in Cluster I and Cluster II, while Cluster I was predominant under LS conditions. Highest inter-cluster distances were between Clusters I and VI in TS (158.70) and Clusters II and V in LS (314.29), indicating substantial genetic divergence. Principal component analysis (PCA) demonstrated that the first three components accounted for 81.48% of the variance in TS conditions and 80.15% in LS conditions. Significant genetic diversity exists among chickpea genotypes, with important traits like seed yield plant-1, plant height and days to 50% flowering contributing to this variation. These findings are relevant for chickpea breeding programs and can aid in selecting genotypes for different sowing conditions.

Keywords

Chickpea, D2 statistics, Genetic diversity, Multivariate, Principal component analysis