Statistical analysis for genotype stability and adaptability in maize yield based on environment and genotype interaction models

Authors

DOI:

https://doi.org/10.5902/2179460X32873

Keywords:

AMMI analysis, GGE biplot, Cultivar recommendations

Abstract

Current analysis investigates genotype x environment interaction and stability performance of grain yield with nine maize genotypes in seven environments. ANOVA revealed highly significant (p-value<0.001) data for genotypes, environments and their interactions. Only PC1 (45.4%) and PC2 (35%) were significant (p ≤ 0.05). Genotype G7 had a specific adaptation to environment E7, whereas genotypes G2 and G3 were adapted to environment E1, and genotypes G8 and G9 to environment E5. Dataset was divided into group A, composed of E5 and E7, and group B composed of E1, E2, E3 and E6. Genotypes G1, G2, G3 and G6, belonging to group B, were the most productive. Further, no environment fell into the G4, G5, G7, G8 and G9 sectors, denoting these genotypes as the poorest ones across environments. GGE biplot indicated that genotype G4 was highly unstable, whereas G3 very stable. In addition, G2 was more desirable due to its small contribution to both G and GE. On the other hand, G4 and G9 were more undesirable due to large contribution to either G or GE. Finally, genotypes G2 and G9 were very different. Their dissimilarity may be due to difference in mean yield and/or in GEI.

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Author Biographies

Nadja Gomes Machado, Instituto Federal de Mato Grosso - IFMT, Campus Cuiabá Bela Vista, Cuiabá, MT

Professora no Instituto Federal de Mato Grosso - IFMT, Campus Cuiabá Bela Vista, Cuiabá, Mato Grosso, Brazil.

Névio Lotufo-Neto, Instituto de Física, Universidade Federal de Mato Grosso - UFMT, Cuiabá, MT

Pós-Graduando na Universidade Federal de Mato Grosso, Instituto de Física, Programa de Pós-Graduação em Física Ambiental, Cuiabá, Mato Grosso, Brazil.

Kuang Hongyu, Universidade Federal de Mato Grosso - UFMT, Cuiabá, MT

Professo na Universidade Federal de Mato Grosso, Departamento de Estatística, Instituto de Ciências Exatas e da Terra, Cuiabá, Mato Grosso, Brazil.

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Published

2019-07-16

How to Cite

Machado, N. G., Lotufo-Neto, N., & Hongyu, K. (2019). Statistical analysis for genotype stability and adaptability in maize yield based on environment and genotype interaction models. Ciência E Natura, 41, e25. https://doi.org/10.5902/2179460X32873

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Statistics

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