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FTIR coupled with chemometrics as a non-invasive tool for PDO olive oils’ discrimination

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datacite.subject.fosCiências Agrárias::Biotecnologia Agrária e Alimentar
datacite.subject.fosCiências Agrárias::Agricultura, Silvicultura e Pescas
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg12:Produção e Consumo Sustentáveis
dc.contributor.authorLamas, Sandra
dc.contributor.authorRuano, Daniela
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorBarreiro, Filomena
dc.contributor.authorPeres, António M.
dc.contributor.authorPereira, José Alberto
dc.date.accessioned2026-03-18T15:10:42Z
dc.date.available2026-03-18T15:10:42Z
dc.date.issued2023
dc.description.abstractQuality schemes protect the diversity of traditional European foods, such as the Protected Designation of Origin (PDO) and the Protected Geographical Indication (PGI). Only the olive oils from extra virgin and virgin commercial categories can be labelled with a PDO or PGI. In Portugal, currently, there are six PDOs. Olive oils labelled as PDO present a superior chemical-sensory quality. Nevertheless, from a commercial point of view it is of paramount importance to be able to identify them according to the correct label, avoiding fraud and ensuring the consumer regarding the exact origin of the purchased oil. Non-invasive and fast techniques, like Fourier transform infrared spectroscopy (FTIR), have been applied to assess olive oil origin and to detect fraud and adulterations. Thus, this work aimed to use FTIR spectra coupled with linear discriminant analysis-simulated annealing algorithm (LDA-SA) to classify commercial olive oils belonging to three Portuguese PDOs, namely, ‘Alentejo Interior’, ‘Beira Interior’, and ‘Trás-os-Montes’. The results showed that a FTIR-LDA-SA model could classify 30 independent oils according to the correct PDO with a sensitivity and specificity of 100% (training, leave-one-out cross-validation) and a sensitivity of 97.5% for the repeated K-fold cross-validation), based on the transmittance values recorded at six selected wavenumbers.eng
dc.description.sponsorshipThe authors thank the Foundation for Science and Technology (FCT, Portugal) for the financial support of the national funds FCT/MCTES to CIMO (UIDB/00690/2020 and UIDP/00690/2020) unit and to the Associate Laboratory SusTEC (LA/P/0007/2020). Nuno Rodrigues thanks the FCTFoundation for Science and Technology, P.I., for the National funding through the institutional program contract for scientific employment. Sandra Lamas also acknowledges the Ph.D. research grant (2022.10070.BD) provided by FCT.
dc.identifier.citationLamas, Sandra; Ruano, Daniela; Rodrigues, Nuno; Barreiro, Filomena; Peres, António M.; Pereira, José Alberto (2023). FTIR coupled with chemometrics as a non-invasive tool for PDO olive oils’ discrimination. In Expoliva XXI Scientific Technical Symposium. p. 1-4. ISBN 978-84-946839-4-7
dc.identifier.isbn978-84-946839-4-7
dc.identifier.urihttp://hdl.handle.net/10198/36137
dc.language.isoeng
dc.peerreviewedyes
dc.relationMountain Research Center
dc.relationMountain Research Center
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relationOliveAged: The influence of olive tree age on fruit-associated endophytes, bioactivity and quality of olive oil of cv. Verdeal Transmontana
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectOlive oil
dc.subjectQuality schemes
dc.subjectFTIR
dc.subjectAuthenticity
dc.titleFTIR coupled with chemometrics as a non-invasive tool for PDO olive oils’ discriminationeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUIDB/00690/2020
oaire.awardNumberUIDP/00690/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardNumber2022.10070.BD
oaire.awardTitleMountain Research Center
oaire.awardTitleMountain Research Center
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardTitleOliveAged: The influence of olive tree age on fruit-associated endophytes, bioactivity and quality of olive oil of cv. Verdeal Transmontana
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/2022.10070.BD/PT
oaire.citation.conferenceDate2023
oaire.citation.conferencePlaceJaén, Espanha
oaire.citation.endPage4
oaire.citation.startPage1
oaire.citation.titleExpoliva XXI Scientific Technical Symposium
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPOR_NORTE
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
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person.familyNamePeres
person.familyNamePereira
person.givenNameSandra
person.givenNameNuno
person.givenNameFilomena
person.givenNameAntónio M.
person.givenNameJosé Alberto
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person.identifier.ciencia-id611F-80B2-A7C1
person.identifier.orcid0000-0002-4334-1636
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person.identifier.orcid0000-0001-6595-9165
person.identifier.orcid0000-0002-2260-0600
person.identifier.ridL-9802-2014
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project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.nameFundação para a Ciência e a Tecnologia
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