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

Detalhes bibliográficos
Autor(a) principal: Brasileiro, Bruno Portela
Data de Publicação: 2016
Outros Autores: Peternelli, Luiz Alexandre, Silveira, Luís Cláudio Inácio, Barbosa, Márcio Henrique Pereira
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Scientiarum. Agronomy (Online)
Texto Completo: http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424
Resumo: The aim of this study was to evaluate the relative importance of agronomic traits during the individual selection in sugarcane (Saccharum spp.), as well as evaluate the potential for using logistic regression and decision trees in identifying the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated in the first test phase (T1) and 659 clones were selected for the second (T2). Logistic regression was applied in both populations (T1 and T2). The number of stalks, bud prominence and length of the internode were the most important traits in selection the T1. Plant vigour, stalk diameter and stalk height were the most important traits in selection the T2. There were 174 individuals selected by the mass selection method in T1 and 113 individuals in T2, while 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. The formulation of decision trees is therefore highly applicable to identifying potential clones in the initial phases of genetic breeding programs.
id UEM-5_00537a17450b6ff937f4ad4ffaccf738
oai_identifier_str oai:periodicos.uem.br/ojs:article/28424
network_acronym_str UEM-5
network_name_str Acta Scientiarum. Agronomy (Online)
repository_id_str
spelling Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regressionImportance of agronomic traits in the individual selection process of sugarcane as determined using logistic regressionSaccharum spp.decision treecrop breedingThe aim of this study was to evaluate the relative importance of agronomic traits during the individual selection in sugarcane (Saccharum spp.), as well as evaluate the potential for using logistic regression and decision trees in identifying the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated in the first test phase (T1) and 659 clones were selected for the second (T2). Logistic regression was applied in both populations (T1 and T2). The number of stalks, bud prominence and length of the internode were the most important traits in selection the T1. Plant vigour, stalk diameter and stalk height were the most important traits in selection the T2. There were 174 individuals selected by the mass selection method in T1 and 113 individuals in T2, while 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. The formulation of decision trees is therefore highly applicable to identifying potential clones in the initial phases of genetic breeding programs.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. Universidade Estadual de Maringá2016-06-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/2842410.4025/actasciagron.v38i3.28424Acta Scientiarum. Agronomy; Vol 38 No 3 (2016); 289-297Acta Scientiarum. Agronomy; v. 38 n. 3 (2016); 289-2971807-86211679-9275reponame:Acta Scientiarum. Agronomy (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424/pdfBrasileiro, Bruno PortelaPeternelli, Luiz AlexandreSilveira, Luís Cláudio InácioBarbosa, Márcio Henrique Pereirainfo:eu-repo/semantics/openAccess2022-02-16T21:48:03Zoai:periodicos.uem.br/ojs:article/28424Revistahttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgronPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/oaiactaagron@uem.br||actaagron@uem.br|| edamasio@uem.br1807-86211679-9275opendoar:2022-02-16T21:48:03Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)false
dc.title.none.fl_str_mv Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
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 in sugarcane determined using the logistic regression
spellingShingle Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
Brasileiro, Bruno Portela
Saccharum spp.
decision tree
crop breeding
title_short Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
title_full Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
title_fullStr Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
title_full_unstemmed Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
title_sort Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
author Brasileiro, Bruno Portela
author_facet Brasileiro, Bruno Portela
Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio
Barbosa, Márcio Henrique Pereira
author_role author
author2 Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio
Barbosa, Márcio Henrique Pereira
author2_role author
author
author
dc.contributor.author.fl_str_mv Brasileiro, Bruno Portela
Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio
Barbosa, Márcio Henrique Pereira
dc.subject.por.fl_str_mv Saccharum spp.
decision tree
crop breeding
topic Saccharum spp.
decision tree
crop breeding
description The aim of this study was to evaluate the relative importance of agronomic traits during the individual selection in sugarcane (Saccharum spp.), as well as evaluate the potential for using logistic regression and decision trees in identifying the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated in the first test phase (T1) and 659 clones were selected for the second (T2). Logistic regression was applied in both populations (T1 and T2). The number of stalks, bud prominence and length of the internode were the most important traits in selection the T1. Plant vigour, stalk diameter and stalk height were the most important traits in selection the T2. There were 174 individuals selected by the mass selection method in T1 and 113 individuals in T2, while 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. The formulation of decision trees is therefore highly applicable to identifying potential clones in the initial phases of genetic breeding programs.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-24
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424
10.4025/actasciagron.v38i3.28424
url http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424
identifier_str_mv 10.4025/actasciagron.v38i3.28424
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424/pdf
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Estadual de Maringá
publisher.none.fl_str_mv Universidade Estadual de Maringá
dc.source.none.fl_str_mv Acta Scientiarum. Agronomy; Vol 38 No 3 (2016); 289-297
Acta Scientiarum. Agronomy; v. 38 n. 3 (2016); 289-297
1807-8621
1679-9275
reponame:Acta Scientiarum. Agronomy (Online)
instname:Universidade Estadual de Maringá (UEM)
instacron:UEM
instname_str Universidade Estadual de Maringá (UEM)
instacron_str UEM
institution UEM
reponame_str Acta Scientiarum. Agronomy (Online)
collection Acta Scientiarum. Agronomy (Online)
repository.name.fl_str_mv Acta Scientiarum. Agronomy (Online) - Universidade Estadual de Maringá (UEM)
repository.mail.fl_str_mv actaagron@uem.br||actaagron@uem.br|| edamasio@uem.br
_version_ 1799305909444280320