Publicação: A Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Crops
dc.contributor.author | Figueredo, Luis | |
dc.contributor.author | Villa-Murillo, Adriana | |
dc.contributor.author | Colmenarez, Yelitza [UNESP] | |
dc.contributor.author | Vasquez, Carlos [UNESP] | |
dc.contributor.institution | Insect Management Sugarcane | |
dc.contributor.institution | Univ Vina del Mar UVM | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.contributor.institution | Tech Univ Ambato UTA | |
dc.date.accessioned | 2021-06-25T11:56:44Z | |
dc.date.available | 2021-06-25T11:56:44Z | |
dc.date.issued | 2021-04-03 | |
dc.description.abstract | Sugarcane 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.affiliation | Insect Management Sugarcane, Yaritagua, Yaracuy State, Venezuela | |
dc.description.affiliation | Univ Vina del Mar UVM, Life Sci Dept, Vina Del Mar, Chile | |
dc.description.affiliation | CABI UNESP FEPAF Fazenda Expt Lageado, Rua Jose Barbosa de Barros 1780, BR-18610307 Botucatu, SP, Brazil | |
dc.description.affiliation | Tech Univ Ambato UTA, Agr Sci Fac, Cevallos, Province Of Tun, Ecuador | |
dc.description.affiliationUnesp | CABI UNESP FEPAF Fazenda Expt Lageado, Rua Jose Barbosa de Barros 1780, BR-18610307 Botucatu, SP, Brazil | |
dc.format.extent | 6 | |
dc.identifier | http://dx.doi.org/10.1093/jisesa/ieab017 | |
dc.identifier.citation | Journal Of Insect Science. Cary: Oxford Univ Press Inc, v. 21, n. 2, 6 p., 2021. | |
dc.identifier.doi | 10.1093/jisesa/ieab017 | |
dc.identifier.uri | http://hdl.handle.net/11449/209339 | |
dc.identifier.wos | WOS:000641632400001 | |
dc.language.iso | eng | |
dc.publisher | Oxford Univ Press Inc | |
dc.relation.ispartof | Journal Of Insect Science | |
dc.source | Web of Science | |
dc.subject | pest insect | |
dc.subject | population management threshold | |
dc.subject | Random Forest | |
dc.subject | genetic algorithm | |
dc.title | A Hybrid Artificial Intelligence Model for Aeneolamia varia (Hemiptera: Cercopidae) Populations in Sugarcane Crops | en |
dc.type | Artigo | pt |
dcterms.license | http://www.oxfordjournals.org/access_purchase/self-archiving_policyb.html | |
dcterms.rightsHolder | Oxford Univ Press Inc | |
dspace.entity.type | Publication | |
unesp.author.orcid | 0000-0002-8214-3632[4] | |
unesp.campus | Universidade Estadual Paulista (UNESP), Faculdade de Ciências Agronômicas, Botucatu | pt |