Fuzzy modeling of the effect of irrigation depths on beet cultivars
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 UNESP |
Texto Completo: | http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022 http://hdl.handle.net/11449/223203 |
Resumo: | The objective of this study was to develop a Fuzzy Rule-Based System (FRBS) for the mathematically modeling of the irrigation level effect on beet cultivars (Beta vulgaris L.). From an agronomic experiment carried out in a protected environment (greenhouse), it was defined as input variables, for each cultivar, the irrigation levels (depths of 25, 40, 55, 70, 85, and 100% of ETc), in which ETc is the crop evapotranspiration [mm d-1], while the output variables were productivity, root diameter, and plant height. Was adopted the inference method of Mamdani and centroid method for fuzzification. The fuzzy models performed better than polynomial regression models, when compared with the coefficients of determination (R²), mean absolute error (MAE) and root mean square error (RMSE). In addition, the excellent performance of the model is highlighted due to the curve containing all the points of the treatments means. As agronomic results, concluded that the Early Wonder cultivar has higher yields when submitted to water deficit. |
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Repositório Institucional da UNESP |
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Fuzzy modeling of the effect of irrigation depths on beet cultivarsArtificial intelligenceBeetFuzzy logicProductionWater deficitThe objective of this study was to develop a Fuzzy Rule-Based System (FRBS) for the mathematically modeling of the irrigation level effect on beet cultivars (Beta vulgaris L.). From an agronomic experiment carried out in a protected environment (greenhouse), it was defined as input variables, for each cultivar, the irrigation levels (depths of 25, 40, 55, 70, 85, and 100% of ETc), in which ETc is the crop evapotranspiration [mm d-1], while the output variables were productivity, root diameter, and plant height. Was adopted the inference method of Mamdani and centroid method for fuzzification. The fuzzy models performed better than polynomial regression models, when compared with the coefficients of determination (R²), mean absolute error (MAE) and root mean square error (RMSE). In addition, the excellent performance of the model is highlighted due to the curve containing all the points of the treatments means. As agronomic results, concluded that the Early Wonder cultivar has higher yields when submitted to water deficit.São Paulo State University (UNESP), SPFederal University of Ceará (UFC), CESão Paulo State University (UNESP), SPUniversidade Estadual Paulista (UNESP)Federal University of Ceará (UFC)Filho, Luís R. A. Gabriel [UNESP]da Silva, Alexsandro O.Cremasco, Camila Pires [UNESP]Putti, Fernando Ferrari [UNESP]2022-04-28T19:49:21Z2022-04-28T19:49:21Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022Engenharia Agricola, v. 42, n. 1, 2022.1808-43890100-6916http://hdl.handle.net/11449/22320310.1590/1809-4430-ENG.AGRIC.V42N1E20210084/20222-s2.0-85122503389Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEngenharia Agricolainfo:eu-repo/semantics/openAccess2022-04-28T19:49:21Zoai:repositorio.unesp.br:11449/223203Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:49:21Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
title |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
spellingShingle |
Fuzzy modeling of the effect of irrigation depths on beet cultivars Filho, Luís R. A. Gabriel [UNESP] Artificial intelligence Beet Fuzzy logic Production Water deficit |
title_short |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
title_full |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
title_fullStr |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
title_full_unstemmed |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
title_sort |
Fuzzy modeling of the effect of irrigation depths on beet cultivars |
author |
Filho, Luís R. A. Gabriel [UNESP] |
author_facet |
Filho, Luís R. A. Gabriel [UNESP] da Silva, Alexsandro O. Cremasco, Camila Pires [UNESP] Putti, Fernando Ferrari [UNESP] |
author_role |
author |
author2 |
da Silva, Alexsandro O. Cremasco, Camila Pires [UNESP] Putti, Fernando Ferrari [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Federal University of Ceará (UFC) |
dc.contributor.author.fl_str_mv |
Filho, Luís R. A. Gabriel [UNESP] da Silva, Alexsandro O. Cremasco, Camila Pires [UNESP] Putti, Fernando Ferrari [UNESP] |
dc.subject.por.fl_str_mv |
Artificial intelligence Beet Fuzzy logic Production Water deficit |
topic |
Artificial intelligence Beet Fuzzy logic Production Water deficit |
description |
The objective of this study was to develop a Fuzzy Rule-Based System (FRBS) for the mathematically modeling of the irrigation level effect on beet cultivars (Beta vulgaris L.). From an agronomic experiment carried out in a protected environment (greenhouse), it was defined as input variables, for each cultivar, the irrigation levels (depths of 25, 40, 55, 70, 85, and 100% of ETc), in which ETc is the crop evapotranspiration [mm d-1], while the output variables were productivity, root diameter, and plant height. Was adopted the inference method of Mamdani and centroid method for fuzzification. The fuzzy models performed better than polynomial regression models, when compared with the coefficients of determination (R²), mean absolute error (MAE) and root mean square error (RMSE). In addition, the excellent performance of the model is highlighted due to the curve containing all the points of the treatments means. As agronomic results, concluded that the Early Wonder cultivar has higher yields when submitted to water deficit. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:49:21Z 2022-04-28T19:49:21Z 2022-01-01 |
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 |
http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022 Engenharia Agricola, v. 42, n. 1, 2022. 1808-4389 0100-6916 http://hdl.handle.net/11449/223203 10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022 2-s2.0-85122503389 |
url |
http://dx.doi.org/10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022 http://hdl.handle.net/11449/223203 |
identifier_str_mv |
Engenharia Agricola, v. 42, n. 1, 2022. 1808-4389 0100-6916 10.1590/1809-4430-ENG.AGRIC.V42N1E20210084/2022 2-s2.0-85122503389 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Engenharia Agricola |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1797789520671801344 |