FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT

Detalhes bibliográficos
Autor(a) principal: Putti,Fernando F.
Data de Publicação: 2017
Outros Autores: Kummer,Ana C. B., Grassi Filho,Helio, Gabriel Filho,Luís R. A., Cremasco,Camila P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000601103
Resumo: ABSTRACT: This study aimed to evaluate the effects of fertilization with composted sewage sludge and irrigation with drinking water (DW) and fertigation with wastewater (WW) in wheat crop using fuzzy rule-based system. The experiment was conducted in the Department of Soil and Environmental Resources, of FCA, UNESP - Botucatu, with factorial 6 × 2, which were applied 6 doses of sewage sludge (0, 50, 100, 150, 200 and 250% of nitrogen recommendation) and two types of effluents (treated water and sewage). In the developing of the system based in fuzzy rules, it was used the Mamdani inference method, where the input variables were sewage sludge doses and water types and the output variables used were the number of tillers, length and number spike per plant; number of spikelet per plant, grain mass per spike and dry mass of the aerial parts. It can be seen that the sewage sludge and the effluent contributed to the higher increase of production, and at 150% sludge dose occurred higher production.
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spelling FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENTsustainabilitynitrogenMamdanifuzzy systemABSTRACT: This study aimed to evaluate the effects of fertilization with composted sewage sludge and irrigation with drinking water (DW) and fertigation with wastewater (WW) in wheat crop using fuzzy rule-based system. The experiment was conducted in the Department of Soil and Environmental Resources, of FCA, UNESP - Botucatu, with factorial 6 × 2, which were applied 6 doses of sewage sludge (0, 50, 100, 150, 200 and 250% of nitrogen recommendation) and two types of effluents (treated water and sewage). In the developing of the system based in fuzzy rules, it was used the Mamdani inference method, where the input variables were sewage sludge doses and water types and the output variables used were the number of tillers, length and number spike per plant; number of spikelet per plant, grain mass per spike and dry mass of the aerial parts. It can be seen that the sewage sludge and the effluent contributed to the higher increase of production, and at 150% sludge dose occurred higher production.Associação Brasileira de Engenharia Agrícola2017-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000601103Engenharia Agrícola v.37 n.6 2017reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v37n6p1103-1115/2017info:eu-repo/semantics/openAccessPutti,Fernando F.Kummer,Ana C. B.Grassi Filho,HelioGabriel Filho,Luís R. A.Cremasco,Camila P.eng2017-11-16T00:00:00Zoai:scielo:S0100-69162017000601103Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2017-11-16T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
title FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
spellingShingle FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
Putti,Fernando F.
sustainability
nitrogen
Mamdani
fuzzy system
title_short FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
title_full FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
title_fullStr FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
title_full_unstemmed FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
title_sort FUZZY MODELING ON WHEAT PRODUCTIVITY UNDER DIFFERENT DOSES OF SLUDGE AND SEWAGE EFFLUENT
author Putti,Fernando F.
author_facet Putti,Fernando F.
Kummer,Ana C. B.
Grassi Filho,Helio
Gabriel Filho,Luís R. A.
Cremasco,Camila P.
author_role author
author2 Kummer,Ana C. B.
Grassi Filho,Helio
Gabriel Filho,Luís R. A.
Cremasco,Camila P.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Putti,Fernando F.
Kummer,Ana C. B.
Grassi Filho,Helio
Gabriel Filho,Luís R. A.
Cremasco,Camila P.
dc.subject.por.fl_str_mv sustainability
nitrogen
Mamdani
fuzzy system
topic sustainability
nitrogen
Mamdani
fuzzy system
description ABSTRACT: This study aimed to evaluate the effects of fertilization with composted sewage sludge and irrigation with drinking water (DW) and fertigation with wastewater (WW) in wheat crop using fuzzy rule-based system. The experiment was conducted in the Department of Soil and Environmental Resources, of FCA, UNESP - Botucatu, with factorial 6 × 2, which were applied 6 doses of sewage sludge (0, 50, 100, 150, 200 and 250% of nitrogen recommendation) and two types of effluents (treated water and sewage). In the developing of the system based in fuzzy rules, it was used the Mamdani inference method, where the input variables were sewage sludge doses and water types and the output variables used were the number of tillers, length and number spike per plant; number of spikelet per plant, grain mass per spike and dry mass of the aerial parts. It can be seen that the sewage sludge and the effluent contributed to the higher increase of production, and at 150% sludge dose occurred higher production.
publishDate 2017
dc.date.none.fl_str_mv 2017-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000601103
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000601103
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v37n6p1103-1115/2017
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.37 n.6 2017
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
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