Path Coefficient, Genetic Divergent and Principal Component Analysis on Common Bean (Phaseolus Vulgaris L.) Genotypes in Sekota, North Western Ethiopia - Assefa, Abebe; Mekonnen, Dereje; Bantayehu, Muluken (Food, Agriculture and Natural Resources - NETWORKS, 2024)
Common bean (Phaseolus vulgaris L.) is a dual purpose, early matured low land pulse crop. Information on the genetic divergent, path coefficient and principal component analysis plays a vital role for further breeding activity in common bean. Therefore, this study was initiated with the objective of identifying superior lines for hybridization program, identify the traits that have direct and indirect effect on seed yield and to determine genetic similarity among genotypes using multivariate analysis on 64 genotypes using 8x8 simple lattice design at Aybra main research site during 2023 under rain fed conditions. Analysis of variance was performed using SAS software and the genetic divergent and principal component analysis were done using R software. The ANOVA revealed highly significant variations among genotypes for all the traits considered in the study and it suggest the possibility of estimating genetic divergent, path coefficient and principal component analysis. Branches per plant, above ground biomass and harvest index had significant positive direct effects on seed yield at the genotypic and phenotypic levels while days to maturity had a significant negative indirect effect with seed yield at the genotypic. The maximum inter cluster distance was found between clusters VII and VIII (D2 =351.39), followed by clusters V and VIII (D2 =331.23). The first five principal component axes accounted for 74.3% of the total variation, with eigenvalues greater than unity. The number of days to maturity, plant height, number of pods per plant, number seeds per pod, seed yield, and harvest index were the traits that contributed most of the variation in the first PCs. Therefore, selection based on direct and indirect effect of the traits and hybridization based on cluster distance could be possible for the improvement of common bean in the study area.