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Statistical methods to study adaptability and stability in breeding lines of food-type soybeans Bragantia
Freiria,Gustavo Henrique; Gonçalves,Leandro Simões Azeredo; Furlan,Felipe Favoretto; Fonseca Junior,Nelson da Silva; Lima,Wilmar Ferreira; Prete,Cássio Egidio Cavenaghi.
ABSTRACT The grains of food-type soybean cultivars, which are characterized by the absence of lipoxygenases and the presence of high levels of proteins and isoflavones, are regarded as functional foods with high acceptance by consumers. However, few cultivars of food-type soybeans are currently available in the Brazilian market. The aim of this work was to study the adaptability and stability of various genotypes of food-type soybeans and to compare the performance of methods, which are based on analysis of variance, non-parametric, regression, multivariate and mixed models. Ten lines of food-type soybeans obtained from the Breeding Program of Soybeans for Human Consumption of the State University of Londrina (UEL/BPSHC) and two commercial varieties, the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Glycine max; Yield; Non-parametric; Regression; Multivariate; Mixed models.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052018000200253
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