Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes

The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the adaptability and stability of three methodologies bas...

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Autores principales:	Moysés Nascimento, Paulo Eduardo Teodoro, Isabela de Castro Sant’Anna, Laís Mayara Azevedo Barroso, Ana Carolina Campana Nascimento, Camila Ferreira Azevedo, Larissa Pereira Ribeiro Teodoro, Francisco José Correia Farias, Helaine Claire Almeida, Luiz Paulo de Carvalho
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	linear regression quantile regression non-parametric regression genotype × environmental interaction Agriculture S
Acceso en línea:	https://doaj.org/article/3a6afbe41c404d4da8ccccd2debd5660
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spelling	oai:doaj.org-article:3a6afbe41c404d4da8ccccd2debd56602021-11-25T16:05:22ZInfluential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes10.3390/agronomy111121792073-4395https://doaj.org/article/3a6afbe41c404d4da8ccccd2debd56602021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4395/11/11/2179https://doaj.org/toc/2073-4395The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the adaptability and stability of three methodologies based on regression in the presence of influential points. Specifically, were evaluated methods based on simple, non-parametric and quantile (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>τ</mi></semantics></math></inline-formula> = 0.50) regressions. The dataset used in this work corresponds to 18 variety trials of cotton cultivars that were conducted in the 2013–2014 and 2014–2015 crop seasons. The evaluated variable was the cotton fiber yield (kg/ha). Once we noticed that the effect of G × E interaction is significant, the statistical procedures adopted for the adaptability and stability analysis of the genotypes. To verify the presence of a possible influential point, we used the leverage values, studentized residuals (SR), DFBETAS and Cook’s distance. As a result, the influential points can modify the recommendation of genotypes, based on regression methods, in the presence of G × E interaction. The non-parametric and quantile (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>τ</mi></semantics></math></inline-formula> = 0.50) regressions, which are based on median estimators, are less sensitive to the presence of influential points avoiding misleading recommendations of genotypes in terms of adaptability.Moysés NascimentoPaulo Eduardo TeodoroIsabela de Castro Sant’AnnaLaís Mayara Azevedo BarrosoAna Carolina Campana NascimentoCamila Ferreira AzevedoLarissa Pereira Ribeiro TeodoroFrancisco José Correia FariasHelaine Claire AlmeidaLuiz Paulo de CarvalhoMDPI AGarticlelinear regressionquantile regressionnon-parametric regressiongenotype × environmental interactionAgricultureSENAgronomy, Vol 11, Iss 2179, p 2179 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	linear regression quantile regression non-parametric regression genotype × environmental interaction Agriculture S
spellingShingle	linear regression quantile regression non-parametric regression genotype × environmental interaction Agriculture S Moysés Nascimento Paulo Eduardo Teodoro Isabela de Castro Sant’Anna Laís Mayara Azevedo Barroso Ana Carolina Campana Nascimento Camila Ferreira Azevedo Larissa Pereira Ribeiro Teodoro Francisco José Correia Farias Helaine Claire Almeida Luiz Paulo de Carvalho Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
description	The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the adaptability and stability of three methodologies based on regression in the presence of influential points. Specifically, were evaluated methods based on simple, non-parametric and quantile (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>τ</mi></semantics></math></inline-formula> = 0.50) regressions. The dataset used in this work corresponds to 18 variety trials of cotton cultivars that were conducted in the 2013–2014 and 2014–2015 crop seasons. The evaluated variable was the cotton fiber yield (kg/ha). Once we noticed that the effect of G × E interaction is significant, the statistical procedures adopted for the adaptability and stability analysis of the genotypes. To verify the presence of a possible influential point, we used the leverage values, studentized residuals (SR), DFBETAS and Cook’s distance. As a result, the influential points can modify the recommendation of genotypes, based on regression methods, in the presence of G × E interaction. The non-parametric and quantile (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>τ</mi></semantics></math></inline-formula> = 0.50) regressions, which are based on median estimators, are less sensitive to the presence of influential points avoiding misleading recommendations of genotypes in terms of adaptability.
format	article
author	Moysés Nascimento Paulo Eduardo Teodoro Isabela de Castro Sant’Anna Laís Mayara Azevedo Barroso Ana Carolina Campana Nascimento Camila Ferreira Azevedo Larissa Pereira Ribeiro Teodoro Francisco José Correia Farias Helaine Claire Almeida Luiz Paulo de Carvalho
author_facet	Moysés Nascimento Paulo Eduardo Teodoro Isabela de Castro Sant’Anna Laís Mayara Azevedo Barroso Ana Carolina Campana Nascimento Camila Ferreira Azevedo Larissa Pereira Ribeiro Teodoro Francisco José Correia Farias Helaine Claire Almeida Luiz Paulo de Carvalho
author_sort	Moysés Nascimento
title	Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
title_short	Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
title_full	Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
title_fullStr	Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
title_full_unstemmed	Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes
title_sort	influential points in adaptability and stability methods based on regression models in cotton genotypes
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3a6afbe41c404d4da8ccccd2debd5660
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_version_	1718413310501584896

Influential Points in Adaptability and Stability Methods Based on Regression Models in Cotton Genotypes

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