Prediction of biological sensors appearance with ARIMA models as a tool for Integrated Pest Management protocols

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Botánicagl
dc.contributor.authorFernández González, María
dc.contributor.authorRamos Valcárcel, David
dc.contributor.authorAira Rodríguez, María Jesús
dc.contributor.authorRodríguez Rajo, Francisco Javier
dc.date.accessioned2017-10-20T22:29:20Z
dc.date.available2017-10-20T22:29:20Z
dc.date.issued2016
dc.description.abstractIntroduction and objectives: Powdery mildew caused by Uncinula necator and Downy mildew produced by Plasmopara viticola are the most common diseases in the North-West Spain vineyards. Knowledge of airborne spore concentrations could be a useful tool in the Integrated Pest Management protocols in order to reduce the number of pesticide treatments, applied only when there is a real risk of infection. Material and Methods: The study was carried out in a vineyard of the D. O. Ribeiro, in the North-West Spain, during the grapevine active period 2004–2012. A Hirts-type volumetric spore-trap was used for the aerobiological monitoring. Results: During the study period the annual total U. necator spores amount ranged from the 578 spores registered in 2007 to the 4,145 spores sampled during 2008. The highest annual total P. viticola spores quantity was observed in 2010 (1,548 spores) and the lowest in 2005 (210 spores). In order to forecast the concentration of fungal spores, ARIMA models were elaborated. Conclusions: The most accurate models were an ARIMA (3.1.3) for U. necator and (1.0.3) for P. viticola. The possibility to forecast the spore presence 72 hours in advance open an important horizon for optimizing the organization of the harvest processes in the vineyardgl
dc.description.peerreviewedSIgl
dc.description.sponsorshipThe study was financed by the Proyects INOU12-08 of the University of Vigo and the AGL2014-60412-R supported by the Ministry of Economy and Competitiveness of the Spanish Governmentgl
dc.identifier.citationFernández-González M, Ramos-Valcárcel D, Jesús Aira M, Rodríguez-Rajo FJ. Prediction of biological sensors appearance with ARIMA models as a tool for Integrated Pest Management protocols. Ann Agric Environ Med. 2016; 23(1): 129–137. doi: 10.5604/12321966.1196868gl
dc.identifier.doi10.5604/12321966.1196868
dc.identifier.essn1898-2263
dc.identifier.issn1232-1966
dc.identifier.urihttp://hdl.handle.net/10347/15921
dc.language.isoenggl
dc.publisherInstitute of Rural Health in Lublin, Polandgl
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2014-60412-R/ES/ESTRATEGIA PARA LA OPTIMIZACION Y EL DESARROLLO SOSTENIBLE DE LA COSECHA DE VARIEDADES AUTOCTONAS DE VID DE LA D.O. RIBEIRO
dc.relation.publisherversionhttps://doi.org/10.5604/12321966.1196868gl
dc.rights© The Author(s) 2016. This work is licensed under a Creative Commons Attribution-NonComercial (CC BY-NC)gl
dc.rights.accessRightsopen accessgl
dc.subjectAgronomygl
dc.subjectARIMAgl
dc.subjectIntegrated pest managementgl
dc.subjectPhytopatologygl
dc.subjectPlasmopara viticolagl
dc.subjectUncinula necatorgl
dc.titlePrediction of biological sensors appearance with ARIMA models as a tool for Integrated Pest Management protocolsgl
dc.typejournal articlegl
dc.type.hasVersionVoRgl
dspace.entity.typePublication
relation.isAuthorOfPublication4e3a2e8e-9727-4508-a86b-5aeb62922659
relation.isAuthorOfPublication.latestForDiscovery4e3a2e8e-9727-4508-a86b-5aeb62922659

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