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| dc.contributor.author | Masresha Gashaw | |
| dc.date.accessioned | 2021-08-12T09:18:17Z | |
| dc.date.available | 2021-08-12T09:18:17Z | |
| dc.date.issued | 2021-08-12 | |
| dc.identifier.uri | http://ir.bdu.edu.et/handle/123456789/12369 | |
| dc.description.abstract | Evaluations of genetic variability is useful for plant breeding and in the development of efficient crop genotypes for different conditions. Eighty-one bread wheat genotypes were tested for 17 agronomic and quality traits in simple lattice design to assess the genetic variability and association among traits at Dabat and Debark research stations of Gondar Agricultural Research Center, during the main cropping season of 2020/21. Analysis of variance revealed the presence of significant differences among genotypes for most of the traits at individual and across locations. From the combined analysis, PCV ranged from 1.50% for starch content to 11.28% for biomass yield, while GCV varied from 0.77% for grain filling period to 9.29% for biomass yield. Moderate to high heritability coupled with moderate genetic advance as percent of the mean was observed for plant height, zeleny sedimentation values, kernel spike-1, biomass yield and wet gluten content across location . Grain yield had positive and significant genotypic correlation with days to maturity, thousand-kernel weight, biomass yield and harvest index. It had positive and significant phenotypic correlation with days to heading, days to maturity, grain filling period, starch content, wet gluten content and hectoliter weight and it showed that negative and significant phenotypic correlation with grain protein content. Genotypic path analysis showed that days to maturity exerted strong positive influence (1.352) on grain yield, followed by biomass yield (1.050). Phenotypic path analysis revealed that days to maturity exerted the highest positive direct effect (2.144) on grain yield followed by harvest index (0.928). Cluster analysis revealed that the 81 genotypes were grouped in five clusters. Genetic distance between clusters showed highly significant difference except between cluster I with II (8.8), III (12.4) and IV (16.1); and II with IV (18.8) and III with IV (17.8) for the characters studied. Moreover, the highest inter-cluster distance was exhibited between cluster I and V (D2 =162.4) indicating that these clusters were genetically more divergent than any other clusters. This shows that there is opportunity to bring improvement through hybridization of genotypes between these clusters and subsequent selection can be made from the segregant generations. Keywords: Cluster analysis; Correlation; Genetic Advance; Heritability and Variability | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Plant Breeding | en_US |
| dc.title | GENETIC VARIABILITY AND ASSOCIATIONS OF TRAITS IN BREAD WHEAT (Triticum aestivum L.) GENOTYPES IN NORTH GONDAR, ETHIOPIA | en_US |
| dc.type | Thesis | en_US |
