GENETIC VARIABILITY OF CHICKPEA (Cicer arietinum L.) GENOTYPES FOR YIELD AND YIELD COMPONENTS IN WEST SHEWA, ETHIOPIA

Ethiopia has a large number of chickpea genotypes/landraces, but all available genotypes have not been evaluated. Hence, the genotype of chickpea was analyzed. The data was collected on days to emergence, days to flowering, days to maturity, grain filling period, plant height, the number of primary and secondary branches, and the number of pods per plant. Analysis of variance showed a highly significant differences (P<0.001) among the evaluated genotypes for all traits considered in the study, indicating the presence of genetic variability. Grain yield was ranged from 7.2–21.95Qnt/ha. Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) was ranged from 1.9 to 36.011% and 2.39 to 36.021%, respectively. High heritability coupled with genetic advances as the percent of mean were noted for traits such as HSW, NSB, HI, GY, BY, NPB, DE, and NPP. Traits like NPB (0.37), NSB (0.476), NPP (0.682), HSW (0.52), BY (0.398) and HI (0.588) had a positive direct effect on grain yield and thus, these traits could serve as selection criteria for improvement of grain yield. In the present study, 56 genotypes are clustered into four clusters where the genotypes in CL-II are the best performing genotypes and followed by CL-III, while genotypes in CL-IV had the least performance. This indicated that parents of different desirable characters can be easily selected from different clusters based on their merit for the breeding program. For instance, genotype(s) can be selected from CL – I for DF, for PH, NPB, NSB, NPP, and NSP, they can be selected from CL – II and from CL– III they can be selected for HSW, GY, BY, DPM and GFP. Principal component analysis showed that the first four PCs with Eigen values greater than one (4.15, 2.59, 1.87, and 1.39) explained about 77% of the total variation among the 56 chickpea genotypes. Characters such as GFP, NSP, HSW, GY, BY, and HI were contributed more for clustering in the first four PCs.