Fuzzy logic applied to simultaneous selection of sweet potato genotypes
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/50815 |
Resumo: | The objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method. |
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Fuzzy logic applied to simultaneous selection of sweet potato genotypesLógica fuzzy aplicada à seleção simultânea de genótipos de batata-doceIpomoea batatasSweet potato - Genetic improvementMultiple selectionComputational intelligenceBatata doce - Melhoramento genéticoSeleção múltiplaInteligência computacionalThe objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method.O objetivo deste trabalho foi realizar a seleção simultânea em genótipos de batata-doce e verificar a eficiência de sistemas fuzzy quando comparados ao método Mulamba & Mock (MM). O experimento foi em blocos casualizados, com 24 genótipos de batata-doce, quatro repetições e dez plantas por parcela. Os valores genéticos foram obtidos pela metodologia dos modelos mistos (REML/BLUP), e posteriormente estimados o índice MM e os ganhos obtidos pelos sistemas fuzzy desenvolvidos. Houve predomínio de efeitos ambientais sobre os efeitos genotípicos para todas as características. Essas estimativas sugerem expressiva contribuição do ambiente para esses caracteres e, consequentemente, maior dificuldade para o melhoramento genético. Através disso, os sistemas fuzzy se destacaram em relação ao método de MM, já que apresentaram ganhos de seleção superiores para os caracteres relacionados à alimentação humana e animal. Os genótipos com potencial para alimentação humana e animal selecionados pelo sistema fuzzy foram: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. A lógica fuzzy foi eficiente na seleção simultânea de genótipos de batata-doce, permitindo a seleção de plantas semelhantes ao ideótipo desejável do que o método MM.Associação Brasileira de Horticultura2022-08-03T21:51:46Z2022-08-03T21:51:46Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108.http://repositorio.ufla.br/jspui/handle/1/50815Horticultura Brasileirareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFernandes, Ana Clara G.Azevedo, Alcinei M.Valadares, Nermy R.Rodrigues, Clóvis H. O.Brito, Orlando G.Andrade Júnior, Valter C. deAspiazú, Ignacioeng2023-05-26T18:55:44Zoai:localhost:1/50815Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T18:55:44Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes Lógica fuzzy aplicada à seleção simultânea de genótipos de batata-doce |
title |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
spellingShingle |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes Fernandes, Ana Clara G. Ipomoea batatas Sweet potato - Genetic improvement Multiple selection Computational intelligence Batata doce - Melhoramento genético Seleção múltipla Inteligência computacional |
title_short |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
title_full |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
title_fullStr |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
title_full_unstemmed |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
title_sort |
Fuzzy logic applied to simultaneous selection of sweet potato genotypes |
author |
Fernandes, Ana Clara G. |
author_facet |
Fernandes, Ana Clara G. Azevedo, Alcinei M. Valadares, Nermy R. Rodrigues, Clóvis H. O. Brito, Orlando G. Andrade Júnior, Valter C. de Aspiazú, Ignacio |
author_role |
author |
author2 |
Azevedo, Alcinei M. Valadares, Nermy R. Rodrigues, Clóvis H. O. Brito, Orlando G. Andrade Júnior, Valter C. de Aspiazú, Ignacio |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Fernandes, Ana Clara G. Azevedo, Alcinei M. Valadares, Nermy R. Rodrigues, Clóvis H. O. Brito, Orlando G. Andrade Júnior, Valter C. de Aspiazú, Ignacio |
dc.subject.por.fl_str_mv |
Ipomoea batatas Sweet potato - Genetic improvement Multiple selection Computational intelligence Batata doce - Melhoramento genético Seleção múltipla Inteligência computacional |
topic |
Ipomoea batatas Sweet potato - Genetic improvement Multiple selection Computational intelligence Batata doce - Melhoramento genético Seleção múltipla Inteligência computacional |
description |
The objective of this work was to perform simultaneous selection in sweet potato genotypes and to verify the efficiency of fuzzy systems when compared to the Mulamba & Mock (MM) method. The experiment was carried out in randomized blocks, with 24 sweet potato genotypes, four replications and ten plants per plot. The breeding values were obtained by the mixed model methodology (REML/BLUP), and then the MM index and the gains obtained by the developed fuzzy systems were estimated. There was a predominance of environmental effects over genotypic effects for all traits. These estimates suggest an expressive contribution of the environment for these traits and, consequently, greater difficulty for genetic improvement. Through this, the fuzzy systems stood out in relation to the MM method, as they presented superior selection gains for characters related to human and animal food. The genotypes with potential for human and animal food selected by the fuzzy system were: UFVJM07, UFVJM05, UFVJM09, UFVJM40, UFVJM01, UFVJM25, UFVJM15. The fuzzy logic was efficient in the simultaneous selection of sweet potato genotypes, allowing the selection of plants similar to the desirable ideotype than the MM method. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-03T21:51:46Z 2022-08-03T21:51:46Z 2022 |
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 |
FERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108. http://repositorio.ufla.br/jspui/handle/1/50815 |
identifier_str_mv |
FERNANDES, A. C. G. et al. Fuzzy logic applied to simultaneous selection of sweet potato genotypes. Horticultura Brasileira, Brasília, DF, v. 40, n. 1, p. 63-70, 2022. DOI: 10.1590/s0102-0536-20220108. |
url |
http://repositorio.ufla.br/jspui/handle/1/50815 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Horticultura |
publisher.none.fl_str_mv |
Associação Brasileira de Horticultura |
dc.source.none.fl_str_mv |
Horticultura Brasileira 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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1807835213673267200 |