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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3418

Title: STATISTICAL ANALYSIS OF GENOTYPE BY ENVIRONMENT INTERACTIONS AND GRAIN YIELD STABILITY IN BREAD WHEAT USING ANOVA AND AMMI MODELS
Authors: Zelalem, Tazu
Advisors: Girma Taye(Dr.)
Keywords: AMMI
Genotype by Environment interaction
Copyright: Jun-2011
Date Added: 18-Jul-2012
Publisher: Addis Ababa University
Abstract: In agricultural experimentation involving Genotype by Environment interactions, a large number of genotypes are normally tested over a wide range of environments and the underlying statistical and genetical theories used to model this system may be rather complicated. The occurrence of the Genotype by Environment interaction further complicates the selection of superior genotypes for a target population of environments. In the absence of Genotype by Environment interaction, the superior genotype in one environment may be regarded as the superior genotype in all, where as the presence of the Genotype by Environment interaction confirms particular genotypes being superior in particular environments. Therefore, Genotype by Environment interaction plays an important role in identifying genotypes for high and stable yield. The goal of this study were to analyze Genotype by Environment interaction and stability of the Ethiopian wheat hybrids for grain yield across the target environments, and to observe the pattern of grouping of the genotypes and the environments based on grain yield response of the hybrids. This study was carried out on the yield performance of 20 bread wheat genotypes across 8 environments in Ethiopia for two growing seasons. The experimental layout was a randomized complete block design with four replications. The combined ANOVA (AMMI ANOVA) showed that environments, genotypes and Genotype by Environment interactions were highly significant (p<0.01) and they accounted for 80.91%, 3.37% and 4.6% of the total variation. The high percentage of the environment is an indication that the major factor that influence yield performance of bread wheat in Ethiopia is the environment. The best fit AMMI model for this multi-environment yield trial data was AMMI-4. Out of the total interactions of principal component analysis (IPCAs), the first four IPCA axes explained 82.63% of the Genotype by Environment interaction sum of squares. However, the biplot (the first two IPCAs) captures 62.32% of the interaction SS. The biplots showed G6, G4 and G9 were more stable genotypes while G10, G20, G16, G18 and G3 were unstable varieties.
Description: A THESIS SUBMITTED TO THE SCHOOL OF GRADUATE STUDIES OF ADDIS ABABA UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTERS OF SCIENCE IN STATISTICS.
URI: http://hdl.handle.net/123456789/3418
Appears in:Thesis - Statistics

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