Genetic variability and association among bread wheat (Triticum aestivum L.) Genotypes for yield and yield related characters in southern ethiopia

Abstract

Although wheat has a long production history in Ethiopia, the mean national yield of the crop is relatively low in contrast with the world average yield due to limited availability of adaptable and stable varieties. Therefore, this study was conducted to estimate genetic variations among 49 bread wheat genotypes and association among yield and related characters to identify superior genotypes. Field experiment was conducted during 2018 cropping season at Kokate and Hossana, Southern Ethiopia. The experimental design used was simple lattice. Data were collected on 12 quantitative and 6 qualitative characters and all quantitative characsters were subjectd to analysis of variance using SAS statistical analysis while qualitative characters were calculated using Shannon index. Analysis of variance across locations revealed significant variations among location, genotype and genotype x location interactions for most of the quantitative characters considered in the study. Shannon index indicated appreciable diversity for most of the qualitative characters studied. The phenotypic coefficient of variation ranged fron 4.78% for plant height to 26.26% for biological yield while the genotypic coefficient of variation ranged from 3.89% for plant height to 23.69% for biological yield. Heritability ranged from 21.15% for number of kernels per spike to 95.31% for days to heading. Heritability along with genetic advance as percent mean for days to heading, biological yield and harvest index, respectively were (95.31, 20.14), (81.40, 24.1) and (84.90, 38.31),showing presence of additive gene and selection based on these characters would be ideal. The correlation analysis revealed number of kernels per spike, biological yield, thousand seed weight and harvest indixe has positive and significant association(P≤ 0.01) with grain yield. Path analysis revealed that biological yield exerted positive direct effect on grain yield both at genotypic and phenotypic levels. Cluster analysis grouped 49 genotypes into five clusters and two solitary groups. The highest inter cluster distance occurred between clusters four and five while the lowest was between clusters two and five. Principal component analysis revealed that five principal components had accounted for 77.6% of the total variation. Generally, the study showed existence of significant genetic variability among tested genotypes. Therefore, simple selection of promising genotypes and crossing of highly divergent group to produce best heterotic offspring could be recommended from the present study . For future breeding programs that employ hybridization, parental material selection should be carried out between clusters rather than within clusters.