2016Journal of Cereals and OilseedsOpen access

Stability analysis of grain yield in rice genotypes across environments of Jimma Zone, Western Ethiopia

Seyou Mulugeta, Sentayehu Alamerew, Kassahun Bantte

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Abstract

Genotype by environment interaction (GEI) is a major complication in plant breeding. An assessment of genotypes across diversified environment and season is important for releasing of varieties. The objective of the study was to evaluate the effects of GEI in fourteen NERICA rice genotype and their adaptation in two years at three locations in the production year 2009 and 2010. The trial was laid out in randomized complete block design with three replications. The combined analysis of variance revealed significant (P<0.01) environments, genotypes and genotype by environment interaction effect and environment captured 91.4% of the total variability. The additive main and multiplicative interaction further explained the genotype by environment interaction by decomposing in to two significant interaction principal components. The fourteen rice genotypes were best explained by the additive main effects and multiplicative interaction (AMMI) 1 that gives model fitness of 98.1%. The polygon view of the Genotype and genotype by environment interaction (GGE) bipolt analysis showed that the environments fall in to two sectors and the genotype NERICA 4 was wining genotypes in all of the environment except E4 (Gomma, 2010). The additive main effect and multiplicative interaction biplot 1 and polygon view of the GGE (Genotype and genotype by environment interaction) biplot showed that the genotype NERICA 4 were consistently higher yielder in all the environments in the study. Key words: Additive main effects and multiplicative interaction (AMMI), Genotype and genotype by environment interaction (GGE), grain yield, upland rice.

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Genotype by environment interaction (GEI) is a major complication in plant breeding. An assessment of genotypes across diversified environment and season is important for releasing of varieties. The objective of the study was to evaluate the effects of GEI in fourteen NERICA rice genotype and their adaptation in two years at three locations in the production year 2009 and 2010. The trial was laid out in randomized complete block design with three replications. The combined analysis of variance revealed significant (P<0.01) environments, genotypes and genotype by environment interaction effect and environment captured 91.4% of the total variability. The additive main and multiplicative interaction further explained the genotype by environment interaction by decomposing in to two significant interaction principal components. The fourteen rice genotypes were best explained by the additive main effects and multiplicative interaction (AMMI) 1 that gives model fitness of 98.1%. The polygon view of the Genotype and genotype by environment interaction (GGE) bipolt analysis showed that the environments fall in to two sectors and the genotype NERICA 4 was wining genotypes in all of the environment except E4 (Gomma, 2010). The additive main effect and multiplicative interaction biplot 1 and polygon view of the GGE (Genotype and genotype by environment interaction) biplot showed that the genotype NERICA 4 were consistently higher yielder in all the environments in the study. Key words: Additive main effects and multiplicative interaction (AMMI), Genotype and genotype by environment interaction (GGE), grain yield, upland rice.

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Available abstract

Genotype by environment interaction (GEI) is a major complication in plant breeding. An assessment of genotypes across diversified environment and season is important for releasing of varieties. The objective of the study was to evaluate the effects of GEI in fourteen NERICA rice genotype and their adaptation in two years at three locations in the production year 2009 and 2010. The trial was laid out in randomized complete block design with three replications. The combined analysis of variance revealed significant (P<0.01) environments, genotypes and genotype by environment interaction effect and environment captured 91.4% of the total variability. The additive main and multiplicative interaction further explained the genotype by environment interaction by decomposing in to two significant interaction principal components. The fourteen rice genotypes were best explained by the additive main effects and multiplicative interaction (AMMI) 1 that gives model fitness of 98.1%. The polygon view of the Genotype and genotype by environment interaction (GGE) bipolt analysis showed that the environments fall in to two sectors and the genotype NERICA 4 was wining genotypes in all of the environment except E4 (Gomma, 2010). The additive main effect and multiplicative interaction biplot 1 and polygon view of the GGE (Genotype and genotype by environment interaction) biplot showed that the genotype NERICA 4 were consistently higher yielder in all the environments in the study. Key words: Additive main effects and multiplicative interaction (AMMI), Genotype and genotype by environment interaction (GGE), grain yield, upland rice.

Key concepts: Ammi, Biplot, Gene–environment interaction, Genotype, Interaction, Main effect, Grain yield, Biology

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