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dc.contributor.authorGonzález-González, María G.
dc.contributor.authorBlasco, José
dc.contributor.authorCubero, Sergio
dc.contributor.authorChueca, Patricia
dc.date.accessioned2021-08-11T10:53:46Z
dc.date.available2021-08-11T10:53:46Z
dc.date.issued2021es
dc.identifier.citationGonzalez-Gonzalez, M. G., Blasco, J., Cubero, S., & Chueca, P. (2021). Automated Detection of Tetranychus urticae Koch in Citrus Leaves Based on Colour and VIS/NIR Hyperspectral Imaging. Agronomy, 11(5), 1002.es
dc.identifier.issn2073-4395
dc.identifier.urihttp://hdl.handle.net/20.500.11939/7545
dc.description.abstractetranychus urticae Koch is an important citrus pest that produces chlorotic spots on the leaves and scars on the fruit of affected trees. It is detected by visual inspection of the leaves. This work studies the potential of colour and hyperspectral imaging (400–1000 nm) under laboratory conditions as a fast and automatic method to detect the damage caused by this pest. The ability of a traditional vision system to differentiate this pest from others, such as Phyllocnistis citrella, and other leaf problems such as those caused by nutritional deficiencies, has been studied and compared with a more advanced hyperspectral system. To analyse the colour images, discriminant analysis has been used to classify the pixels as belonging to either a damaged or healthy leaves. In contrast, the hyperspectral images have been analysed using PLS DA. The rate of detection of the damage caused by T. urticae with colour images reached 92.5%, while leaves that did not present any damage were all correctly identified. Other problems such as damage by P. citrella were also correctly discriminated from T. urticae. Moreover, hyperspectral imaging allowed damage caused by T. urticae to be discriminated from healthy leaves and to distinguish between recent and mature leaves, which indicates whether it is a recent or an older infestation. Furthermore, good results were achieved in the discrimination between damage caused by T. urticae, P. citrella, and nutritional deficiencies.es
dc.language.isoenes
dc.publisherMDPIes
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectTwo-spotted spider mitees
dc.subjectCitrus damagees
dc.subjectOptical sensorses
dc.subjectAutomated monitoring pestes
dc.titleAutomated Detection of Tetranychus urticae Koch in Citrus Leaves Based on Colour and VIS/NIR Hyperspectral Imaginges
dc.typearticlees
dc.authorAddressblasco_josiva@gva.eses
dc.entidadIVIACentro de Agroingenieríaes
dc.identifier.doi10.3390/agronomy11051002es
dc.identifier.urlhttps://www.mdpi.com/2073-4395/11/5/1002es
dc.journal.issueNumber5es
dc.journal.titleAgronomyes
dc.journal.volumeNumber11es
dc.page.final1002es
dc.page.initial1002es
dc.relation.projectIDThis work was partially funded by the Generalitat Valenciana–Instituto Valenciano de Investigaciones Agrarias (GVA-IVIA) project 51918 and the European Regional Development Funds (ERDF).es
dc.rights.accessRightsopenAccesses
dc.source.typeelectronicoes
dc.subject.agrisH10 Pests of plantses
dc.subject.agrisN01 Agricultural engineeringes
dc.subject.agrisN20 Agricultural machinery and equipmentes
dc.subject.agrovocRed spider miteses
dc.subject.agrovocIntegrated pest managementes
dc.subject.agrovocImage processinges
dc.type.hasVersionpublishedVersiones


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