Additive main effects and multiplicative interactions model (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of multi-environmental wheat variety trials

Abstract

Genotype by environment (G×E) interaction is associated with the differential performance of genotypes tested at different locations and in different years, and influences selection and recommendation of cultivars. Wheat genotypes were evaluated in six environments to determine the G×E interactions and stability of the genotypes. Additive main effects and multiplicative interactions (AMMI) was conducted for grain yield of both year and it showed that grain yield variation due to environments, genotypes and (G×E) were highly significant (p <0.01). Stability for grain yield was determined using genotype plus genotype by environment interaction (GGE) biplot analysis. The first two principal components (PC1 and PC2) were used to create a 2-dimensional GGE biplot. Which-wonwhere pattern was based on six locations in the first and five locations in the second year for all the 20 genotypes. The resulting pattern is one realization among many possible outcomes, and its repeatability in the second was different and a future year is quite unknown. A repeatability of whichwon-where pattern over years is the necessary and sufficient condition for mega-environment delineations and genotype recommendation.

Estratificação ambiental e otimização de rede de ensaios de genótipos de soja no Cerrado

“…Porém, independentemente disso, deu-se preferência às estimativas AMMI 1 , seja pelo seu elevado valor preditivo e baixa incorporação de ruídos (Gauch Junior, 1988;Crossa et al, 1991) associados a estratos ambientais mais consistentes, seja para atender às demandas técnica e financeira por reduzido número destes estratos para o desenvolvimento de cultivares e produção de sementes. Por razões semelhantes, modelos com maior número de componentes da interação têm sido preteridos em estudos da interação GxA, em favor da adoção de modelo AMMI 1 (Ebdon & Gauch Junior, 2002;Mortazavian et al, 2014) ou modelo AMMI 2 (Gauch Junior & Zobel, 1996;Ilker et al, 2009). Com a abordagem adotada, a identificação de estratos ambientais ficou condicionada aos genótipos vencedores nos locais de avaliação.…”

“…Essa substituição resultou, quase sempre, em pequena redução (inferior a 2%) da produtividade média dos ambientes para os quais este artifício foi empregado (Figura 1). O artifício é apresentado por Gauch Junior (1992), tendo sido utilizado em outras estratificações ambientais fundamentadas na abordagem de "genótipo vencedor" (Felipe et al, 2010;Mortazavian et al, 2014).…”

“…Assim, são esperadas mudanças nos estratos ambientais, pois a estratificação de uma região depende da interação GxA (Gauch Junior, 1992), com predomínio de interações de natureza complexa ou cruzada (Yan et al, 2007;Negash et al, 2013). Logo, é necessária a revisão periódica do zoneamento ambiental estabelecido.…”

Additive Main Effects and Multiplicative Interactions (AMMI) and genotype by environment interaction (GGE) biplot analyses aid selection of high yielding and adapted finger millet varieties

“…Gauch and Zobel (1996) suggested that the most accurate model for AMMI can be predicted by using the first two IPCAs. Several authors took the first two IPCAs for GGE biplot analysis since because the greater percentage of genotype by environment interaction (GEI), in most cases, were explained by the first IPCA such as for maize (Wonde and Labuschagne, 2005), bread wheat (Yuksel et al, 2002;Farshadfar, 2008;Asnake et al, 2013), common bean (Abeya et al, 2008), for finger millet (Misra et al, 2009) and field pea (Girma et al, 2011). Fig 2).…”

“…Adaptability is the result of genotype, environment and genotype by environment interaction and generally falls into two classes: (1) the ability to perform at an acceptable level in a range of environments, referred to as general adaptability, and (2) the ability to perform well only in desirable environments, known as specific adaptability (Farshadfar and Sutka, 2006). Combined analysis of variance can quantify G x E interactions and describe the main effects but does not explain the interaction effect (Yuksel et al, 2002;Asnake et al, 2013). AMMI model and GGE biplot analysis are the most commonly used analytical and statistical tools to determine the pattern of genotypic responses across environments (Gauch and Zobel, 1996;Yan et al, 2000;Yuksel et al, 2002).…”