2019African Journal of Agricultural ResearchOpen access

Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of large white bean (Phaseolus vulgaris L.) genotypes across environments in Ethiopia

M. Abel, Berhanu Amsalu, Dagmawit Tsegaye

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Abstract

Undertaking a multi-environment trial prior to releasing a high yielding and stable varieties for a specific environment is a major step in plant breeding. Therefore, the objective of this work was to study the effect of Genotype × Environment Interaction (GEI) and evaluate the adaptability and stability of sixteen large white common bean genotypes. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot models were used. The experimental design was 4 × 4 triple lattice across environments. AMMI analysis of variance showed environments that explained the greater proportion (72.42%) of the total variation, followed by GEI (10.75%) and genotype (2.32%). This indicates the possibility of selecting stable genotypes. AMMI biplot analysis revealed that the first and second interaction axes captured 42.62 and 26.77% of the total variation due to GEI. GGE model showed that the nine environments used for the study belonged to two mega-environments. AMMI stability value (ASV), AMMI and GGE biplot identified one common genotype, G14 (SAA 2) that was the overall best in performance in relation to yield and stability. This suggests that for reliability and optimum result it is better to combine the result of two or more analytical tools for yield and stability in recommendation genotype for verification and release. Key words: Biplot, genotype × environment interaction (GEI), grain yield, stability, additive main effects and multiplicative interaction (AMMI), AMMI stability value (ASV).

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What this paper is about

Undertaking a multi-environment trial prior to releasing a high yielding and stable varieties for a specific environment is a major step in plant breeding. Therefore, the objective of this work was to study the effect of Genotype × Environment Interaction (GEI) and evaluate the adaptability and stability of sixteen large white common bean genotypes. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot models were used. The experimental design was 4 × 4 triple lattice across environments. AMMI analysis of variance showed environments that explained the greater proportion (72.42%) of the total variation, followed by GEI (10.75%) and genotype (2.32%). This indicates the possibility of selecting stable genotypes. AMMI biplot analysis revealed that the first and second interaction axes captured 42.62 and 26.77% of the total variation due to GEI. GGE model showed that the nine environments used for the study belonged to two mega-environments. AMMI stability value (ASV), AMMI and GGE biplot identified one common genotype, G14 (SAA 2) that was the overall best in performance in relation to yield and stability. This suggests that for reliability and optimum result it is better to combine the result of two or more analytical tools for yield and stability in recommendation genotype for verification and release. Key words: Biplot, genotype × environment interaction (GEI), grain yield, stability, additive main effects and multiplicative interaction (AMMI), AMMI stability value (ASV).

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Available abstract

Undertaking a multi-environment trial prior to releasing a high yielding and stable varieties for a specific environment is a major step in plant breeding. Therefore, the objective of this work was to study the effect of Genotype × Environment Interaction (GEI) and evaluate the adaptability and stability of sixteen large white common bean genotypes. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot models were used. The experimental design was 4 × 4 triple lattice across environments. AMMI analysis of variance showed environments that explained the greater proportion (72.42%) of the total variation, followed by GEI (10.75%) and genotype (2.32%). This indicates the possibility of selecting stable genotypes. AMMI biplot analysis revealed that the first and second interaction axes captured 42.62 and 26.77% of the total variation due to GEI. GGE model showed that the nine environments used for the study belonged to two mega-environments. AMMI stability value (ASV), AMMI and GGE biplot identified one common genotype, G14 (SAA 2) that was the overall best in performance in relation to yield and stability. This suggests that for reliability and optimum result it is better to combine the result of two or more analytical tools for yield and stability in recommendation genotype for verification and release. Key words: Biplot, genotype × environment interaction (GEI), grain yield, stability, additive main effects and multiplicative interaction (AMMI), AMMI stability value (ASV).

Key concepts: Ammi, Biplot, Main effect, Gene–environment interaction, Interaction, Genotype, Adaptability, Phaseolus

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Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of large white bean (Phaseolus vulgaris L.) genotypes across environments in Ethiopia — Research Paper | ScholarLens