Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil

This work applies the three mode principal components analysis to analyze simultaneously the multiple attributes; to fit of models with additive main effects and multiplicative interaction effects (AMMI models) and the regressions models on sites (SREG models); to evaluate, respectively, the multiva...

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Main Authors: Lúcio Borges de Araújo, Mario Varela Nualles, Mirian Fernandes Carvalho Araújo, Carlos Tadeu dos Santos Dias
Format: Article
Language:English
Published: Wiley 2011-01-01
Series:International Journal of Agronomy
Online Access:http://dx.doi.org/10.1155/2011/215843
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author Lúcio Borges de Araújo
Mario Varela Nualles
Mirian Fernandes Carvalho Araújo
Carlos Tadeu dos Santos Dias
author_facet Lúcio Borges de Araújo
Mario Varela Nualles
Mirian Fernandes Carvalho Araújo
Carlos Tadeu dos Santos Dias
author_sort Lúcio Borges de Araújo
collection DOAJ
description This work applies the three mode principal components analysis to analyze simultaneously the multiple attributes; to fit of models with additive main effects and multiplicative interaction effects (AMMI models) and the regressions models on sites (SREG models); to evaluate, respectively, the multivariate response of the genotype × environment interaction and the mean response of 36 genotypes of corn tested in 4 locations in Brazil. The results were presented by joint plots to identify the best genotypes for their adaptability and performance in the set of attributes.
format Article
id doaj-art-158eea9f121347a791f00c7867a24ab4
institution Kabale University
issn 1687-8159
1687-8167
language English
publishDate 2011-01-01
publisher Wiley
record_format Article
series International Journal of Agronomy
spelling doaj-art-158eea9f121347a791f00c7867a24ab42025-02-03T01:32:47ZengWileyInternational Journal of Agronomy1687-81591687-81672011-01-01201110.1155/2011/215843215843Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of BrazilLúcio Borges de Araújo0Mario Varela Nualles1Mirian Fernandes Carvalho Araújo2Carlos Tadeu dos Santos Dias3Faculty of Mathematics, Federal University of Uberlândia, Avenida João Naves de Ávila, 2.121, 38400-902 Uberlândia, MG, BrazilDepartment of Mathematics, Instituto Nacional de Ciencias Agrícolas (INCA), km 3.5, San José de Las Lajas, 3700 Habana, CubaFaculty of Mathematics, Federal University of Uberlândia, Avenida João Naves de Ávila, 2.121, 38400-902 Uberlândia, MG, BrazilDepartment of Exact Sciences, University of São Paulo, Avenida Pádua Dias, 11, 13418-900 Piracicaba, SP, BrazilThis work applies the three mode principal components analysis to analyze simultaneously the multiple attributes; to fit of models with additive main effects and multiplicative interaction effects (AMMI models) and the regressions models on sites (SREG models); to evaluate, respectively, the multivariate response of the genotype × environment interaction and the mean response of 36 genotypes of corn tested in 4 locations in Brazil. The results were presented by joint plots to identify the best genotypes for their adaptability and performance in the set of attributes.http://dx.doi.org/10.1155/2011/215843
spellingShingle Lúcio Borges de Araújo
Mario Varela Nualles
Mirian Fernandes Carvalho Araújo
Carlos Tadeu dos Santos Dias
Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
International Journal of Agronomy
title Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
title_full Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
title_fullStr Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
title_full_unstemmed Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
title_short Multiattribute Response of Maize Genotypes Tested in Different Coastal Regions of Brazil
title_sort multiattribute response of maize genotypes tested in different coastal regions of brazil
url http://dx.doi.org/10.1155/2011/215843
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