Multivariate Analysis and its Application for Screening Mungbean [Vigna radiata (L.) Wilczek] Landraces

Background: Mungbean [Vigna radiata (L.) Wilczek] is known as one of the important crop Vigna group. In order to determine morphological traits mungbean, multivariate analysis will provide advantages in selection phase future breeding programs. Multivariate statistical was used and classify these traits. analysis, that includes principal component (PCA) cluster (CA), considered best tool for selecting promising genotypes Methods: Eighteen landraces two species were this study. Nine different observed during research period. These are; days 50% flowering (DFT), plant height (PH), branches per (BPP), clusters (CPP), number pods (PPC), seed yield plot (SYPP), biomass (BYPP), harvest index (HI), 1000 weight (SW). Result: Principal revealed a high level variation among genotypes. Therefore, variability DFT (36-59 day), PH (39-76 cm), BPP (3-7), CPP (4-21), SYPP (231-824 g), BYPP (3300-10300 HI (6.77-11.25%) SW (19.95-50.50 g). According with least genetic diversity distance between them terms examined determined 2 3.