Multivariate Analysis and Screening of Moth Bean Accessions for Biotic Stresses in the Arid Region of Western India

The present investigation assesses the genetic diversity and resilience of moth bean (Vigna aconitifolia) against the biotic stresses in the arid zones of India. This research was carried out at the ICAR-Indian Institute of Pulses Research, Regional Research Centre, Bikaner, and employed an augmented design to analyze 300 accessions for morphological and agronomic traits. The study integrated Pearson’s correlation, hierarchical clustering, and principal component analysis to understand trait interrelationships and genetic variance. The number of clusters per plant, number of pods per plant, plant height and test weight showed a highly significant and positive correlation, whereas days to 50% flowering and number of branches per plant showed a negative correlation with seed yield per plant. Hierarchical clustering subdivided accessions into fourteen clusters, and cluster1 best suited to arid conditions with 21 accessions. Principal component analysis with eigenvalues classified the accessions into eight principal components. PC1 contributed the maximum variation that is 32.21 percent, followed by other clusters. Cercospora leaf spot had the highest disease incidence among the three diseases (yellow mosaic virus, cercospora leaf spot and leaf curl virus diseases). The findings underscore the potential of exploiting genetic variability in moth beans for breeding programs aimed at enhancing yield and stress tolerance, crucial for sustainable production in resource-poor arid ecosystems.

Identification of suitable mungbean genotypes for hilly terrains of India using GGE and AMMI biplot approaches

Aim: The present investigation was conducted to approximate the magnitude of genotype × environment interaction effects in mungbean crop and to identify suitable genotypes for northern hilly terrain of India. Methodology: Thirty one promising mungbean genotypes were evaluated in three diverse environments, viz., Srinagar, Berthin and Imphal of northern hilly terrains of India. The individual genotype was planted in 5 rows of 4m length in 3 replications in randomized block design. The statistical analysis was done for Additive Main effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. Results: ANOVA devised that the genotypes, environment and genotype × environment interactions were significant for grain yield. The first two principal components, PC1 and PC2 described 73.65 and 26.35 percent variations, respectively, of total variation. According to AMMI I, the genotypes such as Pant M 6, RMG 1092, TMB 134, CoGG 13-19, KM 2349, DGG-8, TRCM 87-6-2-1, KM 2241 and MDGGv-16 were highly stable genotypes. GGE biplot analysis revealed that Pant M 6 and TMB 134 as winning genotypes for Berthin while NMK 15-12 and MDGGV-16 were the best genotypes for Srinagar. The genotypes IPM 14-7 and GAM 5 were found best for Imphal. Overall, high yield and most stable genotype was DGG-8 for northern hilly terrains of India. Interpretation: GGE biplot and AMMI approach could be instrumental in appraising the genotypes performance in multi-environments/locations testing for efficient selection of the stable genotypes.