Indian Journal of Genetics and Plant Breeding (The)
SCOPUSWeb of Science
  • Year: 2026
  • Volume: 85
  • Issue: 4

Deciphering genetic variation in horse gram [Macrotyloma uniflorum (Lam.) Verdc.] through multivariate analysis

  • Author:
  • Mamta Nehra3*, Rakesh Choudhary3, Ramesh1, Rahul Bhardwaj3, Dan Singh Jakhar3, Praveen Kumar2, Bheru Lal Kumhar3
  • Total Page Count: 10
  • Page Number: 637 to 646

1College of Agriculture, Baytu344 034, Barmer, Agriculture University, Jodhpur, India

2College of Agriculture, Jodhpur342 304, Agriculture University, Jodhpur, India

3Dr. B. R. Choudhary Agricultural Research Station, Mandor342 304, Agricultural University, Jodhpur, Rajasthan, India

*Corresponding Author: Mamta Nehra, Dr. B. R. Choudhary Agricultural Research Station, Mandor342 304, Agricultural University, Jodhpur, Rajasthan, India, E-Mail: mamtanehra089@gmail.com

Abstract

This study evaluated genetic variability, trait associations, and multivariate divergence among fifty horse gram [Macrotyloma uniflorum (Lam.) Verdc.] genotypes using an Augmented Block Design with six checks replicated across three blocks. Data on eight quantitative traits, including seed yield, were analysed through standard statistical methods. Significant variability was observed across all traits, indicating ample scope for selection and improvement. High genotypic and phenotypic coefficients of variation, coupled with high heritability and genetic advance for seed yield and number of pods per plant, emphasized their importance as primary selection criteria. Correlation analysis revealed that seed yield was positively and significantly associated with pods per plant, seeds per pod, days to flowering, and days to maturity, highlighting the role of these traits in yield enhancement. Principal component analysis (PCA) demonstrated that the first two components accounted for more than 62% of the total variation, with PC1 reflecting yield and maturity traits, while PC2 represented seed size and branching. Biplot analysis effectively identified promising genotypes with superior yield attributes and clarified interrelationships among traits. Overall, the study confirmed substantial genetic diversity in horse gram germplasm and identified promising lines with potential for use in breeding programs aimed at yield improvement and adaptability.

Keywords

Horsegram, genetic variability, correlation, principal component analysis (PCA)