Produção Nacional
Adaptability, Stability and Multivariate Selection by Mixed Models
2017; Scientific Research Publishing; Volume: 08; Issue: 13 Linguagem: Inglês
10.4236/ajps.2017.813224
ISSN2158-2750
AutoresAlan Júnior de Pelegrin, Ivan Ricardo Carvalho, Andrei Caíque Pires Nunes, Gustavo Henrique Demari, Vinícius Jardel Szareski, Maurício Horbach Barbosa, Tiago Corazza da Rosa, Maurício Ferrari, Maicon Nardino, Osmarino Pires dos Santos, Marcos Deon Vilela de Resende, Velci Queiróz de Souza, Antônio Costa de Oliveira, Luciano Carlos da Maia,
Tópico(s)Banana Cultivation and Research
ResumoThe aim of this work was to estimate the adaptability and stability of grain yield per hectare and percentage of crude protein of maize grains combined in an index, and to establish a multicharacter selection through mixed models based on an objective character and 15 auxiliary traits. The trials were conducted in the 2013/2014 agricultural year in four growing environments of the Rio Grande do Sul, BR state. The experimental design was randomized blocks arranged in a factorial scheme, being four growing sites × 15 single cross maize hybrids, arranged in three repetitions. The genotypic index, composed by the grain yield and the crude protein percentage in the grains, is the best selection strategy to achieve maize superior genotypes. The multivariate genotypes selection, considering grain yield and crude protein, is efficient. The genotypes FORMULA TL®, AS1656PRO®, P30F53Hx®, LG6304YG® and 30F53 are more adapted and stable for grain yield and percentage of crude protein, in the conditions of this study. The mixed models were efficient to employ the multicharacter selection and to contribute for maize genetic breeding.
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