Legume Research
Web of Science
  • Year: 2026
  • Volume: 49
  • Issue: 4

Identification of Superior Faba bean (Vicia faba L.) Accessions for Key Morphological and Yield-related Traits

  • Author:
  • Yash Kumar Singh1*, Parshuram Sial2, Manoj Kumar3, Thamaraikannan Sivakumar4, Yogesh Kumar1, Ananya Singh5, V.P. Sahi6
  • Total Page Count: 11
  • Page Number: 555 to 565

1Department of Horticulture, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj-211 007, Uttar Pradesh, India.

2Regional Research and Technology Transfer Station, Odisha university of Agriculture and Technology, Semiliguda, Koraput-763 002, Odisha, India.

3Department of Plant Breeding and Genetics, Bihar Agricultural University, Sabour-813 210, Bihar, India.

4Division of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi-110 012, India.

5Department of Plant Pathology, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj-211 007, Uttar Pradesh, India.

6Department of Genetics and Plant Breeding, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj-211 007, Uttar Pradesh, India.

*Corresponding Author: Yash Kumar Singh, Department of Horticulture, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj-211 007, Uttar Pradesh, India. Email: yash.ag@yahoo.com

Abstract

Faba bean (Vicia faba L.) is a multipurpose legume whose genetic improvement relies on exploiting existing morphological variation. Rigorous phenotypic evaluation provides insights into heritability, trait associations and divergence patterns, which are crucial for identifying superior genotypes and its selections in breeding programs.

Forty-five genotypes, including three checks, were evaluated across two Rabi seasons in a randomized block design for 20 agro-morphological traits spanning phenology, plant architecture, pod/seed attributes and yield. Best Linear Unbiased Estimates (BLUEs) were computed across replications and seasons.Broad-sense heritability. Genotypic variation, genetic divergence, D2 statistics, trait associations and the multi-trait Genotype-Ideotype Distance Index (MGIDI) were applied to identify superior accessions.

Analysis of variance showed significant genotypic variation for most of the traits, with high heritability. However, leaflet width and seeds per pod had moderate heritability. Mahalanobis D2 divided genotypes into four clusters. Cluster IV displayed strong yield traits and significant differences from Cluster I, indicating potential for hybrid vigour. Correlation analysis revealed positive relationships, such as maturity with pods per plant and pod length, along with some trade-offs. MGIDI found nine promising accessions that combine earliness, good pod and seed traits and appealing structure. Overall, these results confirm a wide range of phenotypic diversity and provide a clear set of accession for improving faba bean.

Keywords

Best linear unbiased estimates, Cluster analysis, Faba bean, Heritability, Multi-trait genotype-ideotype distance index (MGIDI), Phenotypic selection