Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression

The aim of this study was to evaluate the importance of agronomic traits during the selection of sugarcane (Saccharum spp.), as well as to evaluate the potential for using logistic regression and decision trees to identify the best genotypes. A total of 7,719 seedlings of 128 half-sib families were...

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Autores: Brasileiro, Bruno Portela, Peternelli, Luiz Alexandre, Silveira, Luís Cláudio Inácio da, Barbosa, Márcio Henrique Pereira
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:Brasil
Institución:Universidade Federal de Viçosa (UFV)
Repositorio:LOCUS Repositório Institucional da UFV
Idioma:inglés
OAI Identifier:oai:locus.ufv.br:123456789/26312
Acceso en línea:http://dx.doi.org/10.4025/actasciagron.v38i3.28424
http://locus.ufv.br//handle/123456789/26312
Access Level:acceso abierto
Palabra clave:Saccharum spp.
Decision tree
Crop breeding
Árvore de decisão
Melhoramento genético
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spelling Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regressionSaccharum spp.Decision treeCrop breedingÁrvore de decisãoMelhoramento genéticoThe aim of this study was to evaluate the importance of agronomic traits during the selection of sugarcane (Saccharum spp.), as well as to evaluate the potential for using logistic regression and decision trees to identify the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated during the first test phase (T1), and 659 clones were selected for the second (T2). Logistic regression was applied to both populations. The number of stalks, bud prominence and length of the internode were the most important selection traits in the T1 population. The plant vigor, stalk diameter and stalk height were the most important selection traits in the T2 population. There were 174 individuals selected when using the mass selection method in T1 and 113 individuals in T2, whereas a logistic regression selected 153 individuals in T1 and 79 in T2. The apparent error rates of the logistic models fitted to the selections in T1 and T2 were 0.8 and 5.10%, respectively. By using a decision tree, 67 clones were selected among the most productive ones in phase T2. Therefore, the formulation of decision trees is highly applicable to identifying potential clones during the initial phases of breeding programs.O objetivo desse trabalho foi avaliar a importância dos caracteres agronômicos durante o processo de seleção individual em cana-de-açúcar, além de avaliar o potencial do uso da regressão logística e da árvore de decisão na identificação dos melhores genótipos. Foram avaliados 7.719 seedlings na primeira fase de teste (T1) e 659 clones na segunda fase de teste (T2). Os caracteres número de colmos, saliência da gema e comprimento do entre-nó foram os de maior importância no processo de seleção massal realizado no T1. Vigor da planta, diâmetro de colmo e altura de colmo foram os mais importantes na seleção do T2. Pelo método massal foram selecionados 174 indivíduos no T1 e 113 no T2, enquanto a regressão logística selecionou 153 indivíduos no T1 e 79 no T2. A taxa de erro aparente dos modelos logísticos ajustados para as seleções no T1 e T2 foram de 0,8 e 5,10%, respectivamente. Com o uso da árvore de decisão foram selecionados 67 clones dentre os mais produtivos na fase T2. A elaboração de árvores de decisão apresenta grande aplicabilidade na identificação de clones potenciais nas fases iniciais dos programas de melhoramento genético da cana-de-açúcar.Acta Scientiarum. Agronomy2019-07-23T13:42:16Z2019-07-23T13:42:16Z2016-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlepdfapplication/pdf1807-8621http://dx.doi.org/10.4025/actasciagron.v38i3.28424http://locus.ufv.br//handle/123456789/26312engv. 38, n. 3, p. 289- 297, jul.- set. 2016info:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVBrasileiro, Bruno PortelaPeternelli, Luiz AlexandreSilveira, Luís Cláudio Inácio daBarbosa, Márcio Henrique Pereira2024-07-12T08:43:17Zoai:locus.ufv.br:123456789/26312Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452024-07-12T08:43:17LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
title Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
spellingShingle Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
Brasileiro, Bruno Portela
Saccharum spp.
Decision tree
Crop breeding
Árvore de decisão
Melhoramento genético
title_short Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
title_full Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
title_fullStr Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
title_full_unstemmed Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
title_sort Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
dc.creator.none.fl_str_mv Brasileiro, Bruno Portela
Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio da
Barbosa, Márcio Henrique Pereira
author Brasileiro, Bruno Portela
author_facet Brasileiro, Bruno Portela
Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio da
Barbosa, Márcio Henrique Pereira
author_role author
author2 Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio da
Barbosa, Márcio Henrique Pereira
author2_role author
author
author
dc.subject.por.fl_str_mv Saccharum spp.
Decision tree
Crop breeding
Árvore de decisão
Melhoramento genético
topic Saccharum spp.
Decision tree
Crop breeding
Árvore de decisão
Melhoramento genético
description The aim of this study was to evaluate the importance of agronomic traits during the selection of sugarcane (Saccharum spp.), as well as to evaluate the potential for using logistic regression and decision trees to identify the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated during the first test phase (T1), and 659 clones were selected for the second (T2). Logistic regression was applied to both populations. The number of stalks, bud prominence and length of the internode were the most important selection traits in the T1 population. The plant vigor, stalk diameter and stalk height were the most important selection traits in the T2 population. There were 174 individuals selected when using the mass selection method in T1 and 113 individuals in T2, whereas a logistic regression selected 153 individuals in T1 and 79 in T2. The apparent error rates of the logistic models fitted to the selections in T1 and T2 were 0.8 and 5.10%, respectively. By using a decision tree, 67 clones were selected among the most productive ones in phase T2. Therefore, the formulation of decision trees is highly applicable to identifying potential clones during the initial phases of breeding programs.
publishDate 2016
dc.date.none.fl_str_mv 2016-07
2019-07-23T13:42:16Z
2019-07-23T13:42:16Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 1807-8621
http://dx.doi.org/10.4025/actasciagron.v38i3.28424
http://locus.ufv.br//handle/123456789/26312
identifier_str_mv 1807-8621
url http://dx.doi.org/10.4025/actasciagron.v38i3.28424
http://locus.ufv.br//handle/123456789/26312
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv v. 38, n. 3, p. 289- 297, jul.- set. 2016
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv Acta Scientiarum. Agronomy
publisher.none.fl_str_mv Acta Scientiarum. Agronomy
dc.source.none.fl_str_mv reponame:LOCUS Repositório Institucional da UFV
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str LOCUS Repositório Institucional da UFV
collection LOCUS Repositório Institucional da UFV
repository.name.fl_str_mv LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv fabiojreis@ufv.br
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score 15.301603

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