Fuzzy modeling of the effects of irrigation and water salinity in harvest point of tomato crop. Part I: Description of the method

dc.contributor.authorNeto, Daniel dos S.Viais
dc.contributor.authorCremasco, Camila P. [UNESP]
dc.contributor.authorBordin, Deyver [UNESP]
dc.contributor.authorPutti, Fernando F. [UNESP]
dc.contributor.authorJunior, Josué F.Silva
dc.contributor.authorFilho, Luís R. A. Gabriel [UNESP]
dc.contributor.institutionSão Paulo State Faculty of Technology (FATEC)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionFederal University of the Triângulo Mineiro
dc.date.accessioned2019-10-06T15:47:22Z
dc.date.available2019-10-06T15:47:22Z
dc.date.issued2019-05-01
dc.description.abstractIt was used statistical techniques for the evaluation of agricultural experiments, but there are mathematical theories that allow finer adjustments, highlighting among them, the fuzzy logic. The objective of the study was characterizing a method of fuzzy modeling from an agronomic experiment. For this study it was used data from an experiment conducted at the School of Agriculture of São Paulo State University (UNESP) in Botucatu-SP. The system input variables based in fuzzy rules were soil water tension and doses of water salinity, being defined three fuzzy sets. The output variables was elected from the biometric and productivity analysis that showed statistically significant differences, namely, plant height, stem diameter, leaf area, green biomass, dry weight, number of fruits, average fruit weight and percentage of disabled fruits. For output variables 9 fuzzy sets were defined. From the adopted methodology, the model allowed extract directly from the data set a base of rules without the use of questionnaires to experts for its preparation. In addition, it will analyze intermediate regions at trial levels and weave other conclusions of the tomato growth and productivity, not limiting in this way only those observed with statistical analysis.en
dc.description.affiliationSão Paulo State Faculty of Technology (FATEC)
dc.description.affiliationSão Paulo State University (UNESP) School of Sciences and Engineering
dc.description.affiliationSão Paulo State University (UNESP) School of Agriculture
dc.description.affiliationFederal University of the Triângulo Mineiro
dc.description.affiliationUnespSão Paulo State University (UNESP) School of Sciences and Engineering
dc.description.affiliationUnespSão Paulo State University (UNESP) School of Agriculture
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipUniversidade Estadual Paulista
dc.description.sponsorshipIdCNPq: 313570/2017-5
dc.format.extent294-304
dc.identifierhttp://dx.doi.org/10.1590/1809-4430-Eng.Agric.v39n3p294-304/2019
dc.identifier.citationEngenharia Agricola, v. 39, n. 3, p. 294-304, 2019.
dc.identifier.doi10.1590/1809-4430-Eng.Agric.v39n3p294-304/2019
dc.identifier.fileS0100-69162019000300294.pdf
dc.identifier.issn1808-4389
dc.identifier.issn0100-6916
dc.identifier.scieloS0100-69162019000300294
dc.identifier.scopus2-s2.0-85067653611
dc.identifier.urihttp://hdl.handle.net/11449/187790
dc.language.isoeng
dc.relation.isnodouble190899*
dc.relation.ispartofEngenharia Agricola
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectCrop management
dc.subjectDrought
dc.subjectFuzzy logic
dc.subjectSalt stress
dc.titleFuzzy modeling of the effects of irrigation and water salinity in harvest point of tomato crop. Part I: Description of the methoden
dc.typeArtigo
unesp.author.lattes9951953532998797[2]
unesp.author.orcid0000-0002-7269-2806[6]
unesp.author.orcid0000-0003-2465-1361[2]

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