Adaptability

Genotype x environment interaction for morpho-agronomic traits and color parameters in cassava in the Central Amazon

E. I. Costa, Ticona-Benavente, C. A., and Filho, D. Fda Silva, “Genotype x environment interaction for morpho-agronomic traits and color parameters in cassava in the Central Amazon”, Genetics and Molecular Researcn, vol. 21, no. 4, 2022.

Genealogical and genomic heritability for adaptability and reproductive traits in the Colombian Creole cattle breeds Blanco Orejinegro and Sanmartinero

C. De León, Martínez, R., and Rocha, J. F., “Genealogical and genomic heritability for adaptability and reproductive traits in the Colombian Creole cattle breeds Blanco Orejinegro and Sanmartinero”, Genetics and Molecular Research, vol. 20, no. 3, 2021.

Colored fiber cotton in the Uberlândia region using artificial neural networks for yield assessment

D. B. O. Cardoso, Júnior, E. G. Silva, Reis, M. C., de Sousa, L. B., Falco, L. M. S., Mamede, M. C., Machado, B. Q. V., Paiva, T. S., Gundim, C. P., and Alves, G. A., “Colored fiber cotton in the Uberlândia region using artificial neural networks for yield assessment”, Genetics and Molecular Research, vol. 18, no. 1, 2019.

Factor analysis using mixed models of multi-environment trials with different levels of unbalancing

J. J. Nuvunga, Oliveira, L. A., Pamplona, A. K. A., Silva, C. P., Lima, R. R., and Balestre, M., “Factor analysis using mixed models of multi-environment trials with different levels of unbalancing”, vol. 14, pp. 14262-14278, 2015.

This study aimed to analyze the robustness of mixed models for the study of genotype-environment interactions (G x E). Simulated unbalancing of real data was used to determine if the method could predict missing genotypes and select stable genotypes. Data from multi-environment trials containing 55 maize hybrids, collected during the 2005-2006 harvest season, were used in this study.

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