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dc.creatorPérez Roncal, Claudiaes_ES
dc.creatorLópez Maestresalas, Ainaraes_ES
dc.creatorLópez Molina, Carloses_ES
dc.creatorJarén Ceballos, Carmenes_ES
dc.creatorUrrestarazu Vidart, Jorgees_ES
dc.creatorSantesteban García, Gonzagaes_ES
dc.creatorArazuri Garín, Silviaes_ES
dc.date.accessioned2020-01-14T09:21:14Z
dc.date.available2020-01-14T09:21:14Z
dc.date.issued2020
dc.identifier.issn2073-4395
dc.identifier.urihttps://hdl.handle.net/2454/36056
dc.description.abstractPowdery mildew is a worldwide major fungal disease for grapevine, which adversely affects both crop yield and produce quality. Disease identification is based on visible signs of a pathogen once the plant has already been infected; therefore, techniques that allow objective diagnosis of the disease are currently needed. In this study, the potential of hyperspectral imaging (HSI) technology to assess the presence of powdery mildew in grapevine bunches was evaluated. Thirty Carignan Noir grape bunches, 15 healthy and 15 infected, were analyzed using a lab-scale HSI system (900–1700 nm spectral range). Image processing was performed to extract spectral and spatial image features and then, classification models by means of Partial Least Squares Discriminant Analysis (PLS-DA) were carried out for healthy and infected pixels distinction within grape bunches. The best discrimination was achieved for the PLS-DA model with smoothing (SM), Standard Normal Variate (SNV) and mean centering (MC) pre-processing combination, reaching an accuracy of 85.33% in the cross-validation model and a satisfactory classification and spatial location of either healthy or infected pixels in the external validation. The obtained results suggested that HSI technology combined with chemometrics could be used for the detection of powdery mildew in black grapevine bunches.en
dc.description.sponsorshipThis research received funding from the Department of Economic Development of the Navarre Government (Project: DECIVID (Res.104E/2017)), by the Spanish Ministry of Economy and Competitiveness (Project TIN2016-77356-P) and by the research services of the Universidad Pública de Navarra. C.P.-R is a beneficiary of postgraduate scholarships funded by Universidad Pública de Navarra (FPI-UPNA-2017 (Res.654/2017)).en
dc.format.extent16 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherMDPIen
dc.relation.ispartofAgronomy 2020, 10, 88en
dc.rights© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectImage analysisen
dc.subjectNIR-HSIen
dc.subjectChemometricsen
dc.subjectFungal diseaseen
dc.subjectVitis vinifera L.en
dc.titleHyperspectral imaging to assess the presence of powdery mildew (Erysiphe necator) in cv. Carignan Noir grapevine bunchesen
dc.typeArtículo / Artikuluaes
dc.typeinfo:eu-repo/semantics/articleen
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Ingenieríaes_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Ingeniaritza Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticases_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematikak Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Agronomía, Biotecnología y Alimentaciónes_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Agronomia, Bioteknologia eta Elikadura Sailaeu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.doi10.3390/agronomy10010088
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-Pen
dc.relation.publisherversionhttps://doi.org/10.3390/agronomy10010088
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.contributor.funderGobierno de Navarra / Nafarroako Gobernua, Proyecto DECIVID (Res.104E/2017)es
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, FPI-UPNA-2017 (Res.654/2017)es


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license
Except where otherwise noted, this item's license is described as © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license