Hyperspectral imaging to assess the presence of powdery mildew (Erysiphe necator) in cv. Carignan Noir grapevine bunches

dc.contributor.authorPérez Roncal, Claudia
dc.contributor.authorLópez Maestresalas, Ainara
dc.contributor.authorLópez Molina, Carlos
dc.contributor.authorJarén Ceballos, Carmen
dc.contributor.authorUrrestarazu Vidart, Jorge
dc.contributor.authorSantesteban García, Gonzaga
dc.contributor.authorArazuri Garín, Silvia
dc.contributor.departmentIngenieríaes_ES
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentAgronomía, Biotecnología y Alimentaciónes_ES
dc.contributor.departmentIngeniaritzaeu
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.departmentAgronomia, Bioteknologia eta Elikaduraeu
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
dc.date.accessioned2020-01-14T09:21:14Z
dc.date.available2020-01-14T09:21:14Z
dc.date.issued2020
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.identifier.doi10.3390/agronomy10010088
dc.identifier.issn2073-4395
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/36056
dc.language.isoengen
dc.publisherMDPIen
dc.relation.ispartofAgronomy 2020, 10, 88en
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-P/
dc.relation.publisherversionhttps://doi.org/10.3390/agronomy10010088
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.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://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.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
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