Sugarcane families selection in early stages based on classification by discriminant linear analysis

Detalhes bibliográficos
Autor(a) principal: Moreira, Édimo Fernando Alves
Data de Publicação: 2015
Outros Autores: Peternelli, Luiz Alexandre
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/13964
Resumo: A major challenge in breeding programs is the efficient selection of genotypes in the early stages. The efficiency of selection in these phases is critical for the program targets, since, due to the particularity of sugarcane, the genotypes selected in the early stages will be assessed in later stages. The objective of this study was to compare selection by linear discriminant analysis with family selection based on estimates of the variable tons of cane per hectare (TCHe), defined by the indirect traits number of stalks, stalk diameter and stalk height, as alternatives to the selection of promising sugarcane families. Also simulations were considered in order to augment the training observations before analysis. Five different simulation scenarios were considered: without simulation and with 500, 750, 1000, or 2000 families simulated. The methods were compared and evaluated by the apparent error rate (AER). Linear discriminant analysis indicated a high concordance with the selection based on the measured, or real, TCH (TCHr) and can be used for early selection of sugarcane families. In the simulated scenarios, results from selection based on linear discriminant analysis were better than those of selection for TCHe. The AER is minimized when 1,000 families are simulated to augment the training observations.
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spelling Sugarcane families selection in early stages based on classification by discriminant linear analysisSeleção precoce entre famílias de cana-de-açúcar via classificação por análise discriminante linearSimulationPlant breedingSaccharum spp.SimulaçãoMelhoramento de plantasA major challenge in breeding programs is the efficient selection of genotypes in the early stages. The efficiency of selection in these phases is critical for the program targets, since, due to the particularity of sugarcane, the genotypes selected in the early stages will be assessed in later stages. The objective of this study was to compare selection by linear discriminant analysis with family selection based on estimates of the variable tons of cane per hectare (TCHe), defined by the indirect traits number of stalks, stalk diameter and stalk height, as alternatives to the selection of promising sugarcane families. Also simulations were considered in order to augment the training observations before analysis. Five different simulation scenarios were considered: without simulation and with 500, 750, 1000, or 2000 families simulated. The methods were compared and evaluated by the apparent error rate (AER). Linear discriminant analysis indicated a high concordance with the selection based on the measured, or real, TCH (TCHr) and can be used for early selection of sugarcane families. In the simulated scenarios, results from selection based on linear discriminant analysis were better than those of selection for TCHe. The AER is minimized when 1,000 families are simulated to augment the training observations.RESUMO: Um dos grandes desafios nos programas de melhoramento genético de cana-de-açúcar é a seleção eficiente de genótipos nas fases iniciais. Uma seleção eficiente nestas fases é de suma importância para os objetivos do programa, uma vez que, devido á particularidade da cana-deaçúcar, os materiais selecionados na fase inicial serão avaliados nas etapas posteriores. O objetivo deste trabalho é comparar a seleção via análise discriminante linear e a seleção de famílias usando a variável tonelada de cana por hectare estimada (TCHe) com base nos caracteres indiretos número de colmos, diâmetro de colmos e altura de colmos como alternativas para seleção de famílias promissoras em cana-de-açúcar. Também foi considerado o uso de simulação para aumento do conjunto de treinamento previamente a análise. As análises foram realizadas em cinco diferentes cenários, definidos em função do número de valores simulados: sem simulação, com simulação de valores para 500, 750, 1000 e 2000 famílias. Para comparação e avaliação dos métodos empregados foi utilizada a taxa de erro aparente (TEA). A análise discriminante linear apresenta alta concordância com a seleção via TCHr podendo ser utilização para seleção precoce entre famílias em cana-de-açúcar. Nos cenários onde houve simulação, a análise discriminante linear tem desempenho superior a seleção via TCHe. A taxa de erro aparente é minimizada quando pelo menos 1.000 famílias são utilizadas para o aumento da população de treinamento.Universidade Federal de Lavras2015-12-292017-08-01T20:09:52Z2017-08-01T20:09:52Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfapplication/pdfMOREIRA, E. F. A.; PETERNELLI, L. A. Sugarcane families selection in early stages based on classification by discriminant linear analysis. Revista Brasileira de Biometria, Lavras, v. 33, n. 4, p. 484-493, dez. 2015.http://repositorio.ufla.br/jspui/handle/1/13964REVISTA BRASILEIRA DE BIOMETRIA; Vol 33 No 4 (2015); 484-4931983-0823reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttp://www.biometria.ufla.br/index.php/BBJ/article/view/28/16Copyright (c) 2015 Édimo Fernando Alves MOREIRA, Luiz Alexandre PETERNELLIAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessMoreira, Édimo Fernando AlvesPeternelli, Luiz AlexandreMoreira, Édimo Fernando AlvesPeternelli, Luiz Alexandre2021-04-16T14:36:46Zoai:localhost:1/13964Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-04-16T14:36:46Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Sugarcane families selection in early stages based on classification by discriminant linear analysis
Seleção precoce entre famílias de cana-de-açúcar via classificação por análise discriminante linear
title Sugarcane families selection in early stages based on classification by discriminant linear analysis
spellingShingle Sugarcane families selection in early stages based on classification by discriminant linear analysis
Moreira, Édimo Fernando Alves
Simulation
Plant breeding
Saccharum spp.
Simulação
Melhoramento de plantas
title_short Sugarcane families selection in early stages based on classification by discriminant linear analysis
title_full Sugarcane families selection in early stages based on classification by discriminant linear analysis
title_fullStr Sugarcane families selection in early stages based on classification by discriminant linear analysis
title_full_unstemmed Sugarcane families selection in early stages based on classification by discriminant linear analysis
title_sort Sugarcane families selection in early stages based on classification by discriminant linear analysis
author Moreira, Édimo Fernando Alves
author_facet Moreira, Édimo Fernando Alves
Peternelli, Luiz Alexandre
author_role author
author2 Peternelli, Luiz Alexandre
author2_role author
dc.contributor.author.fl_str_mv Moreira, Édimo Fernando Alves
Peternelli, Luiz Alexandre
Moreira, Édimo Fernando Alves
Peternelli, Luiz Alexandre
dc.subject.por.fl_str_mv Simulation
Plant breeding
Saccharum spp.
Simulação
Melhoramento de plantas
topic Simulation
Plant breeding
Saccharum spp.
Simulação
Melhoramento de plantas
description A major challenge in breeding programs is the efficient selection of genotypes in the early stages. The efficiency of selection in these phases is critical for the program targets, since, due to the particularity of sugarcane, the genotypes selected in the early stages will be assessed in later stages. The objective of this study was to compare selection by linear discriminant analysis with family selection based on estimates of the variable tons of cane per hectare (TCHe), defined by the indirect traits number of stalks, stalk diameter and stalk height, as alternatives to the selection of promising sugarcane families. Also simulations were considered in order to augment the training observations before analysis. Five different simulation scenarios were considered: without simulation and with 500, 750, 1000, or 2000 families simulated. The methods were compared and evaluated by the apparent error rate (AER). Linear discriminant analysis indicated a high concordance with the selection based on the measured, or real, TCH (TCHr) and can be used for early selection of sugarcane families. In the simulated scenarios, results from selection based on linear discriminant analysis were better than those of selection for TCHe. The AER is minimized when 1,000 families are simulated to augment the training observations.
publishDate 2015
dc.date.none.fl_str_mv 2015-12-29
2017-08-01T20:09:52Z
2017-08-01T20:09:52Z
2017-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv MOREIRA, E. F. A.; PETERNELLI, L. A. Sugarcane families selection in early stages based on classification by discriminant linear analysis. Revista Brasileira de Biometria, Lavras, v. 33, n. 4, p. 484-493, dez. 2015.
http://repositorio.ufla.br/jspui/handle/1/13964
identifier_str_mv MOREIRA, E. F. A.; PETERNELLI, L. A. Sugarcane families selection in early stages based on classification by discriminant linear analysis. Revista Brasileira de Biometria, Lavras, v. 33, n. 4, p. 484-493, dez. 2015.
url http://repositorio.ufla.br/jspui/handle/1/13964
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.biometria.ufla.br/index.php/BBJ/article/view/28/16
dc.rights.driver.fl_str_mv Copyright (c) 2015 Édimo Fernando Alves MOREIRA, Luiz Alexandre PETERNELLI
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Édimo Fernando Alves MOREIRA, Luiz Alexandre PETERNELLI
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv REVISTA BRASILEIRA DE BIOMETRIA; Vol 33 No 4 (2015); 484-493
1983-0823
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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