1Department of Horticulture, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
2Department of Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
3Department of Microbiology, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
4Department of Floriculture and Landscape Architecture, Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
*Corresponding Author: S. Karthikeyan, Department of Floriculture and Landscape Architecture, Horticultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India, Email: hortikarthik@tnau.ac.in Orcid ID: 0000-0001-7416-9982.
Online published on 19 November, 2024.
Broad bean (Vicia faba L.) is an important protein rich underutilized vegetable crop cultivated for its tender green pods and dry seeds. The present study was carried out to assess the genetic divergence among the broad bean genotypes collected for developing high-yielding cultivars.
The experimental material consisted of 20 broad bean genotypes, raised in randomized block design with three replications at Horticultural Research Station, Nilgiris, Tamil Nadu, India during Kharif 2023. Data concerning 12 quantitative traits and 7 qualitative traits underwent examination using Mahalanobis D2 statistic, principal component analysis and stepwise multiple regression analysis.
The cluster analysis categorized the genotypes into nine clusters, with the highest number of genotypes in Cluster II (4) and the lowest in Clusters VII, VIII and IX (1 each). Cluster IV displayed the highest intra-cluster distance (D2=3358.2), signifying substantial variation among the genotypes within this cluster. The largest inter-cluster distance (D2=316.9) was observed between Clusters I and VII, indicating significant divergence from other clusters, suggesting that genotypes within these clusters could be valuable as diverse parents for hybridization and selection. The PCA combined with stepwise multiple regression analysis highlighted the primary variations and traits influencing pod yield.
Mahalanobis D2, PCA, Regression analysis