Abstract:
The field experiment was conducted to assess the extent of genetic variability and traits associations in soybean genotypes for yield and its related traits and thereby generate information as well as identify superior genotypes for further improvement program. A total of thirty-six soybean genotypes were evaluated using simple lattice design at Fedis eastern Ethiopia during the 2018 cropping season. Data were recorded for major qualitative and quantitative traits and analyzed using appropriate statistical software. Analysis of variance revealed that the genotypes were highly significant for all the traits studied, indicating the existence of a considerable magnitude of variability. High values of phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), broad-sense heritability (H2), and genetic advance as percent of mean (GAM) were estimated for plant height, primary branches per plant, pod per plant, seeds per pod, and grain yield indicating the ease of direct selection for the improvement of these traits. Most of the traits showed positive correlations among themselves both at phenotypic and genotypic levels. Grain yield had a highly significant and positive genotypic and phenotypic correlation with primary branches per plant, pods per plant, seeds per pod and plant height, indicating that simultaneous improvement of the grain yields with the associated traits is favorable. Plant height exerted the highest genotypic (0.74) and phenotypic (0.54) direct effect on grain yield, followed by hundred seeds weight and number of pods per plant showed higher genotypic direct effect on grain yield. This indicated that attention should be given for these traits primarily for direct and indirect selection for variety development. The first three PCA explained 74.75% of the total variation and traits such as pods per plant (0.78), grain yield (0.72), primary branches per plant (0.52), seeds per pod (0.40) and plant height (0.39) accounted for most of the variability in the first principal component. The tested genotypes exhibited a wide range of variability for most of the traits and they were clustered into four groups based on resemblance and difference. Furthermore, in order to get more reliable information on the variability and identify high yielding varieties, repeating the trial across more locations is required.
