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Publicação:
A Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Crops

dc.contributor.authorFigueredo, Luis
dc.contributor.authorVilla-Murillo, Adriana
dc.contributor.authorColmenarez, Yelitza [UNESP]
dc.contributor.authorVasquez, Carlos [UNESP]
dc.contributor.institutionInsect Management Sugarcane
dc.contributor.institutionUniv Vina del Mar UVM
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionTech Univ Ambato UTA
dc.date.accessioned2021-06-25T11:56:44Z
dc.date.available2021-06-25T11:56:44Z
dc.date.issued2021-04-03
dc.description.abstractSugarcane spittlebugs are considered important pests in sugarcane crops ranging from the southeastern United States to northern Argentina. To evaluate the effects of climate variables on adult populations of Aeneolamia varia (Fabricius) (Hemiptera: Cercopidae), a 3-yr monitoring study was carried out in sugarcane fields at week-long intervals during the rainy season (May to November 2005-2007). The resulting data were analyzed using the univariate Forest-Genetic method. The best predictive model explained 75.8% variability in physiological damage threshold. It predicted that the main climatic factors influencing the adult population would be, in order of importance, evaporation; evapotranspiration by 0.5; evapotranspiration, cloudiness at 2:00 p.m.; average sunshine and relative humidity at 8:00 a.m. The optimization of the predictive model established that the lower and upper limits of the climatic variables produced a threshold in the population development rate of 184 to 267 adult insects under the agroecological conditions of the study area.These results provide a new perspective on decision-making in the preventive management of A. varia adults in sugarcane crops.en
dc.description.affiliationInsect Management Sugarcane, Yaritagua, Yaracuy State, Venezuela
dc.description.affiliationUniv Vina del Mar UVM, Life Sci Dept, Vina Del Mar, Chile
dc.description.affiliationCABI UNESP FEPAF Fazenda Expt Lageado, Rua Jose Barbosa de Barros 1780, BR-18610307 Botucatu, SP, Brazil
dc.description.affiliationTech Univ Ambato UTA, Agr Sci Fac, Cevallos, Province Of Tun, Ecuador
dc.description.affiliationUnespCABI UNESP FEPAF Fazenda Expt Lageado, Rua Jose Barbosa de Barros 1780, BR-18610307 Botucatu, SP, Brazil
dc.format.extent6
dc.identifierhttp://dx.doi.org/10.1093/jisesa/ieab017
dc.identifier.citationJournal Of Insect Science. Cary: Oxford Univ Press Inc, v. 21, n. 2, 6 p., 2021.
dc.identifier.doi10.1093/jisesa/ieab017
dc.identifier.urihttp://hdl.handle.net/11449/209339
dc.identifier.wosWOS:000641632400001
dc.language.isoeng
dc.publisherOxford Univ Press Inc
dc.relation.ispartofJournal Of Insect Science
dc.sourceWeb of Science
dc.subjectpest insect
dc.subjectpopulation management threshold
dc.subjectRandom Forest
dc.subjectgenetic algorithm
dc.titleA Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Cropsen
dc.typeArtigopt
dcterms.licensehttp://www.oxfordjournals.org/access_purchase/self-archiving_policyb.html
dcterms.rightsHolderOxford Univ Press Inc
dspace.entity.typePublication
unesp.author.orcid0000-0002-8214-3632[4]
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências Agronômicas, Botucatupt

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