Adaptability and stability of maize hybrids in unreplicated multienvironment trials

Diego Coelho dos Santos, Carlos Henrique Pereira, José Airton Rodrigues Nunes, André Luiz Lepre


In maize breeding programs conducted by private companies, it is common to perform the product advanced trials (PAT) in several cultivation environments in order to better recommend the new hybrids, as well as to provide opportunities for the farmers to evaluate their products. The aim of this study was to describe the adaptability and stability of maize hybrids from unreplicated PATs using a multivariate approach combined with univariate methods. We considered the grain yield data of twelve maize hybrids evaluated in a PATs network conducted by the company DuPont Pioneer in 80 cultivation environments in the states of Minas Gerais and Goias, in second-crop of 2014. The AMMI analysis was employed and additionally we applied the methods based on bisegmented linear regression, Lin and Binns index (1988) and Annicchiarico index (1992). Significant differences were verified among the tested hybrids. The macro-environmental variation and the effect of hybrid by environment (H x E) interaction were expressive. The application of the AMMI method allowed the study of the H x E interaction based on maize PATs. Hybrids 7 and 8 are recommended for higher quality environments, while hybrids 3, 5 and 12 present wide adaptability. The Lin and Binns (1988) and Annicchiarico (1992) indexes highlight the hybrid 8 as the most promising for associating high productivity and lower risk in the tested cultivation environments.


Zea mays; Product Advancement Trials; Genotype by Environment Interaction; AMMI; Reliability Index

Texto completo:



ALVARES, C. A. et al. Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift, v. 22, n. 6, p. 711-728, 2013.

ANNICCHIARICO, P. Cultivar adaptation and recommendation from alfafa trials in Northern Italy. Journal Genetics and Breeding, v. 46, n. 1, p. 269-278, 1992.

CARGNELUTTI FILHO, A. et al. Comparação de métodos de adaptabilidade e estabilidade relacionados à produtividade de grãos de cultivares de milho. Bragantia, v. 66, n. 4, p. 571-578, 2007.

CRUZ, C. D.; TORRES, R. A.; VENCOVSKY, R.. An alternative approach to the stability analysis proposed by Silva and Barreto. Revista Brasileira de Genética, v. 12, n. 3, p. 567-580, 1989.

DUARTE, J. B.; VENCOVSKY, R. Interação genótipos x ambientes: uma introdução a analise “AMMI”. Ribeirão Preto: Sociedade Brasileira de Genética, 1999. 60 p.

EBERHART, S. A.; RUSSELL, W. A. Stability parameters for comparing varieties. Crop Science, v. 6, n. 1, p. 36-40, 1966.

FARIA, S. V. et al. Adaptability and stability in commercial maize hybrids in the southeast of the State of Minas Gerais, Brazil. Revista Ciência Agronômica, v. 48, n. 2, p. 347-357, 2017.

FERREIRA, D. F. Sistemas de análises estatísticas 3.0. Lavras: FAEPE/UFLA/PEX, 2000.

FERREIRA, D. F. et al. Statistical models in agriculture: biometrical methods for evaluating phenotypic stability in plant breeding. Cerne, v. 12, n. 4, p. 373-388, 2006.

GAUCH JUNIOR, H. G. A simple protocol for AMMI analysis of yield trials. Crop Science, v. 53, n. 5, p. 1860-1869, 2013.

JOHANNES, F; PIEPHO, H. P. Parametric bootstrap methods for testing multiplicative terms in GGE and AMMI models. Biometrics, v. 70, n. 3, p. 1541-0420, 2014.

LIN, C. S.; BINNS, M. R. A superiority measure of cultivar performance for cultivar x location data. Canadian Journal of Plant Science, v. 68, n. 1, p. 193-198, 1988.

MACHADO, J. C. et al. Estabilidade de produção de híbridos simples e duplos de milho oriundos de um mesmo conjunto gênico. Bragantia, v. 67, n. 3, p. 627-631, 2008.

MILLIKEN, G. A.; JOHNSON, D. E. Analysis of messy data. New York: Chapman & Hall: CRC, 2000. v. 2, 199 p.

OLIVEIRA, R. L. et al. Evaluation of maize hybrids and environmental

stratification by the methods AMMI and GGE biplot. Crop Breeding and Applied Biotechnology, v. 10, n. 3, p. 247-253, 2010.

NDHLELA, T. et al. Genotype × environment interaction of maize grain yield using AMMI Biplots. Crop Science, v. 54, n. 5, p. 1992-1999, 2014.

PADEREWSKI, J. et al. AMMI analysis of four-way genotype x location x management x year data from a wheat trial in Poland. Crop Science, v. 56, p. 2157-2164, 2016.

R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2016.

RAMALHO, M. A. P. et al. Contributions of plant breeding in Brazil: progress and perspectives. Crop Breeding and Applied Biotechnology, v. 12, p. 111-120, 2012. Número especial.

VAN EEUWIJK, F. A. et al. What should students in plant breeding know about the statistical aspects of genotype X environment interactions? Crop Science, v. 56, n. 5, p. 2119-2140, 2016.

Revista Ciência Agronômica ISSN 1806-6690 (online) 0045-6888 (impresso), Site:, e-mail: - Fone: (85) 3366.9702 - Expediente: 2ª a 6ª feira - de 7 às 17h.