Mungbean (Vigna radiata (L.) R. Wilczek var. radiata) is a highly nutritious legume grown in diverse cropping systems. However, its productivity is often hindered by abiotic stresses, particularly drought, which significantly impacts yield during critical growth stages such as flowering and pod filling. With climate change projected to increase drought frequency, leguminous crops are expected to be more vulnerable, exacerbating food security concerns. This study aimed to identify drought-tolerant mungbean genotypes by evaluating 122 genotypes (116 minicore accessions and six check varieties) under well-watered (WW) and drought-stressed (DS) conditions in a semi-controlled pot culture setup. Drought tolerance was assessed using multiple stress indices (e.g., STI, GMP), principal component analysis (PCA), and the multi-trait genotype-ideotype distance index (MGIDI). Significant genetic variability was observed across both WW and DS conditions, with drought stress leading to reductions in grain yield (21.1%), leaf area (35.4%), canopy greenness (32.1%), and photosynthetic rate (51.8%). Traits such as plant height, number of branches, pods per plant, seeds per pod, transpiration rate, and grain yield showed high heritability and genetic advance, indicating strong breeding potential. PCA analysis identified major traits contributing to drought tolerance, including yield-related traits and physiological responses, such as transpiration rate, stomatal conductance, and photosynthetic efficiency. MGIDI effectively identified 18 genotypes based on multi-trait performance. Among them, genotypes VI003685AG, VI002051BG, VI000852AG, VI002402BG, and VI003957AG consistently ranked as top performers across both traditional indices and MGIDI, demonstrating preliminary drought tolerance. The integration of stress indices, PCA, and MGIDI provided a comprehensive approach to genotype selection, offering potentially valuable genetic resources for future mungbean breeding programs targeting drought-prone environments. However, these findings are preliminary and require multi-location field validation before breeding use.
Basavaraj et al. (Thu,) studied this question.