Journal of Environmental Biology

Genetic variability, association and principal component analysis for agronomical traits in mungbean (Vigna radiata L. Wilczek)

A. Mishra¹, C.M. Singh¹, V. Sharma¹, H. Kumar¹, Kamaluddin¹, G. Shukla² and M. Kumar¹*      

¹Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda-210 001, India

²Department of Agricultural Statistics, Banda University of Agriculture and Technology, Banda-210 001, India

Received: 09 July 2024                   Revised: 09 November 2024                   Accepted: 06 January 2025

*Corresponding Author Email : mukulbreeder@rediffmail.com                    *ORCiD: https://orcid.org/0000-0002-3716-4258

Abstract

Aim: This study aimed to assess the extent of genetic variability in 205 diverse green gram genotypes for agronomical traits and to identify the most effective traits for consideration in development of high yielding cultivars in mungbean.

Methodology: The 205 diverse genotype including five checks of mungbean were evaluated in augmented block design-I with eight blocks. In each block, the 30 genotypes (25 genotypes + 5 checks) were grown in paired rows of 4 m length with 45 x 10 cm spacing. The mean data from selected plants across all the genotypes and checks were analyzed for genetic variability parameters (PCV, GCV, h²_bs, GAM), Correlation, Path Analysis and Principal Component Analysis (PCA).

Results: The high estimates of genotypic coefficient of variation, phenotypic coefficient of variation, heritability (h²_bs) along with high genetic advance over mean were observed for number of branches per plant, number of clusters per plant, number of pods per cluster,number of pods per plant and seed yield per plant. The present study indicated that seed yield per plant had significant and positive correlation with harvest index, biological yield per plant, number of pods per plant and number of pods per cluster, and also highly influenced by these traits both directly and indirectly. PCA analysis revealed that out of thirteen principal components, five Pcs (PC1 to  PC5) had eigenvalue of >1.0 explaining 19.20%, 16.10%, 11.90%, 10.70% and 8.10%, respectively, accounted for 66% of total variation indicated the strong association of PCs and traits studied. PCA suggested that traits such as vegetative period, number of clusters per plant, number of pods per cluster, number of pods per plant and harvest index were the principal discriminatory traits.

Interpretation: It is suggested that selection based on harvest index, biological yield per plant, number of pods per plant and number of pods per cluster may result in improvement of seed yield in mungbean.

Key words: Correlation analysis, Genetic variability, Mungbean, Path analysis, Principal component analysis

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