2017Vavilov Journal of Genetics and BreedingOpen access

AMMI and GGE biplot analyses of genotype-environment interaction in spring barley lines

П Н Солонечный

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Abstract

Yield stability depends on the resistance of varieties and hybrids to stressful environmental factors. Assessment of genotype-environment interaction helps breeders select the best genotypes for submission to the state variety trials. The article presents results of AMMI (Additive Main effects and Multiplicative Interaction) and GGE (Genotype plus Genotype-Environment interaction) biplot analyses of the grain yield data in eight promising spring barley lines bred at the Plant Production Institute nd. a V.Ya. Yuryev of NAAS and two standard varieties in 2012–2015. The objective of this study was to determine the effect of genotype, environment and their interaction for grain yield and identify stable and performance genotypes. The experimental layout was randomized complete block design with four replications. The analysis of variance on grain yield data showed that the mean squares of environments, genotypes and genotype-environment interaction (GEI) accounted for 85.8, 8.1 and 6.1 % of treatment combination sum of squares, respectively. To find out the effects of GEI on grain yield, the data were subjected to AMMI and GGE biplot analysis. The AMMI model presented greater efficiency by retaining most of the variation in the first two main components, 95.7 %, followed by the GGE biplot model, 82.9 %. Lines 09-837 (G8) and 08-1385 (G9) presented an elevated grain yield and stability as determined by the AMMI and GGE biplot methodologies. These lines named as “Avgur” and “Veles” were submitted to the state variety trial. The results finally indicated that AMMI and GGE biplot are informative methods to explore stability and adaptation pattern of genotypes in practical plant breeding and in subsequent variety recommendations.

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Yield stability depends on the resistance of varieties and hybrids to stressful environmental factors. Assessment of genotype-environment interaction helps breeders select the best genotypes for submission to the state variety trials. The article presents results of AMMI (Additive Main effects and Multiplicative Interaction) and GGE (Genotype plus Genotype-Environment interaction) biplot analyses of the grain yield data in eight promising spring barley lines bred at the Plant Production Institute nd. a V.Ya. Yuryev of NAAS and two standard varieties in 2012–2015. The objective of this study was to determine the effect of genotype, environment and their interaction for grain yield and identify stable and performance genotypes. The experimental layout was randomized complete block design with four replications. The analysis of variance on grain yield data showed that the mean squares of environments, genotypes and genotype-environment interaction (GEI) accounted for 85.8, 8.1 and 6.1 % of treatment combination sum of squares, respectively. To find out the effects of GEI on grain yield, the data were subjected to AMMI and GGE biplot analysis. The AMMI model presented greater efficiency by retaining most of the variation in the first two main components, 95.7 %, followed by the GGE biplot model, 82.9 %. Lines 09-837 (G8) and 08-1385 (G9) presented an elevated grain yield and stability as determined by the AMMI and GGE biplot methodologies. These lines named as “Avgur” and “Veles” were submitted to the state variety trial. The results finally indicated that AMMI and GGE biplot are informative methods to explore stability and adaptation pattern of genotypes in practical plant breeding and in subsequent variety recommendations.

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Available abstract

Yield stability depends on the resistance of varieties and hybrids to stressful environmental factors. Assessment of genotype-environment interaction helps breeders select the best genotypes for submission to the state variety trials. The article presents results of AMMI (Additive Main effects and Multiplicative Interaction) and GGE (Genotype plus Genotype-Environment interaction) biplot analyses of the grain yield data in eight promising spring barley lines bred at the Plant Production Institute nd. a V.Ya. Yuryev of NAAS and two standard varieties in 2012–2015. The objective of this study was to determine the effect of genotype, environment and their interaction for grain yield and identify stable and performance genotypes. The experimental layout was randomized complete block design with four replications. The analysis of variance on grain yield data showed that the mean squares of environments, genotypes and genotype-environment interaction (GEI) accounted for 85.8, 8.1 and 6.1 % of treatment combination sum of squares, respectively. To find out the effects of GEI on grain yield, the data were subjected to AMMI and GGE biplot analysis. The AMMI model presented greater efficiency by retaining most of the variation in the first two main components, 95.7 %, followed by the GGE biplot model, 82.9 %. Lines 09-837 (G8) and 08-1385 (G9) presented an elevated grain yield and stability as determined by the AMMI and GGE biplot methodologies. These lines named as “Avgur” and “Veles” were submitted to the state variety trial. The results finally indicated that AMMI and GGE biplot are informative methods to explore stability and adaptation pattern of genotypes in practical plant breeding and in subsequent variety recommendations.

Key concepts: Biplot, Ammi, Main effect, Gene–environment interaction, Grain yield, Interaction, Randomized block design, Biotechnology

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