Legume Research
Web of Science
  • Year: 2025
  • Volume: 48
  • Issue: 12

Integrating Diversity Analysis and Morphological Characterization for Strategic Trait Selection in Advanced Breeding Lines of Chickpea (Cicer arietinum L.)

  • Author:
  • Teena Patel1,*, Anita Babbar1, Karishma Behera1, Jai Kumar Anand1, Monika Patel1, Monica Jyoti Kujur1, Vijay Kumar Katara1
  • Total Page Count: 10
  • Page Number: 1969 to 1978

1Department of Genetics and Plant Breeding, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur-482 004, Madhya Pradesh, India

*Corresponding Author: Teena Patel, Department of Genetics and Plant Breeding, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur-482 004, Madhya Pradesh, India, Email: teenapateljbp@gmail.com

Online published on 29 January, 2026.

Abstract

The depleting genetic diversity in cultivated chickpea highlights the need to identify and integrate novel variations into breeding programs. Morphological characterization remains a crucial tool for identifying elite lines with desirable traits, offering key insights for strategic crop improvement. The integration of morphological characterization with various methods of diversity assessment provides a robust framework for identifying genotypes with significant phenotypic diversity across key morphological traits.

The investigation was carried out during the Rabi seasons of 2022-2023 and 2023-2024 under three different sowing conditions, aiming to characterize thirty advanced breeding lines of desi chickpea according to DUS guidelines. Various analyses such as shannon weaver diversity index, principle component analysis, hierarchical clustering and phylogenetic assessment were integrated to identify diverse lines across all the traits studied.

Significant phenotypic variability was observed for most of the traits. PCA revealed that first five components with Eigen values greater than one contributed to a maximum of 76.34 per cent of the variability with lines JG2016-9651, JG2022-2 and ICCV191609 being diverse for the multiple traits across several PCs. Hierarchical clustering analysis grouped genotypes into six clusters, with cluster III being the largest. Genotypes JG2020-55, ICCV181109, JG2022-12, ICCV191609 and JG2016-9651 showed the highest inter-cluster distances, indicating significant genetic divergence. Phylogenetic analysis validated these findings revealing six clusters and provided further insights into the genetic relationships and evolutionary divergence among the genotypes.

Keywords

Chickpea, Clustering, DUS guidelines, PCA