Deciphering genetic variability and phenotype expression, assessing drought stress tolerance and multi-trait stability index of (Vigna radiata) genotypes in Chitwan, Nepal

Abstract

Grappling with climate change, and delving into variability among mung germplasm offers genetic stock. Therefore, harnessing RCB design, 16 mung genotypes were assessed in field & control environments through punctilious mixed models, and Duncan’s test (p ≤ 0.05) to assess stress indicators and yield attributes. This study divulges that 4 qualitative traits with a Shannon diversity index ranging from 0.41 to 0.74; 12 eigenvalues >1 contributed to 73% of variability. Likewise, the first 3 PCs accounted for variances: 19.25%, 8.39%, and 6.97%. From root architecture to yield attributes was captured in 3 PCs. Besides, elbow technique revealed that 4- clusters have a dissimilarity coefficient of 0.18; and disparate intra and inter-cluster distances, 440.6 (I) and 5959.402 (I-II), harbingering invaluable for hybridization. Path analysis revealed a positive association—post fertility traits & yield. Further, Duncan’s test elucidated that VC6370A, ideal in grain yield (2.432 tons/ha), subsequently CN95 (2.272 tons/ha). VC3960A-88 has the highest SPAD value (66.13), but Seedlings of VC6368 (46-40-3) is more apt to heat & drought-tolerant; in contrast, VC6370A has a deep root architecture, accentuating genes for water use efficiency & climate-resilient breeding. To add, MTSI disclose that VC6848, VC1973A(SC) were selected as stable & promising for improvement.

Keywords

• Phenotypic markers
• multivariate selection
• climate-resilient breeding
• genetic variation
• mung-bean
• Agriculture & Environmental Sciences