Sugarcane families selection in early stages based on classification by discriminant linear analysis
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
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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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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1815439340332908544 |