TITLE:
Adaptability, Stability and Multivariate Selection by Mixed Models
AUTHORS:
Alan Junior de Pelegrin, Ivan Ricardo Carvalho, Andrei Caíque Pires Nunes, Gustavo Henrique Demari, Vinicíus Jardel Szareski, Mauricio Horbach Barbosa, Tiago Corazza da Rosa, Mauricio Ferrari, Maicon Nardino, Osmarino Pires dos Santos, Marcos Deon Vilela de Resende, Velci Queiróz de Souza, Antonio Costa de Oliveira, Luciano Carlos da Maia
KEYWORDS:
Plant Breeding, Zea mays L., Phenotypic Index, Genetic Parameters, Multicharacter
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.8 No.13,
December
14,
2017
ABSTRACT: The 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.