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Fourier transform infrared spectroscopy-chemometric approach as a non-destructive olive cultivar tool for discriminating Portuguese monovarietal olive oils

2021Journal article Open access
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dc.contributor.authorLamas, Sandra
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorFernandes, Isabel P.
dc.contributor.authorBarreiro, M.F.
dc.contributor.authorPereira, J.A.
dc.contributor.authorPeres, António M.
dc.date.accessioned2018-02-19T10:00:00Z
dc.date.accessioned2021-11-23T09:39:57Z
dc.date.available2018-01-19T10:00:00Z
dc.date.available2021-11-23T09:39:57Z
dc.date.issued2021
dc.description.abstractFour Portuguese monovarietal olive oils (cvs. Cobrançosa, Madural, Santulhana and Verdeal Transmontana) were evaluated, totalizing 24 independent samples. Olive cultivar significantly influenced (P values lt 0.05, one-way ANOVA) the oils’ physicochemical and sensory attributes, fulfilling all oils the legal thresholds for extra-virgin classification. Oils from cv. Verdeal Transmontana had the highest oxidative stability (16.9 ± 1.0 h), whereas cvs. Cobrançosa and Santulhana oils have the highest total phenols content (204 ± 30 and 177 ± 33 mg GAE/kg, respectively). Concerning the sensory attributes, only cv. Santulhana oils fitted fruity greenly oils type, presenting, in general, significantly higher olfactory and gustatory intensities (P values lt 0.05, one-way ANOVA), with a higher number of perceived sensory attributes (e.g., herbaceous sensations), compared to the other monovarietal oils. Free acidity, peroxide value, extinction coefficients, total phenols and oxidative stability allowed the unsupervised differentiation (principal component analysis, PCA) of the four monovarietal oils, and in a less extent, the sensory data. Fourier transform infrared (FTIR) spectroscopy-chemometric procedure was developed based on raw or transformed forms of the recorded spectra. Raw, 1st and 2nd derivative spectra allowed the unsupervised (PCA) and supervised (linear discriminant analysis, LDA) identification of the olive cultivar of the studied oils. In fact, FTIR-LDA models, based on the raw transmittance or on their 1st or 2nd derivatives, recorded at 5, 4 or 3 selected wavenumbers, respectively, allowed to correctly classify all oils (sensitivities greater than 99 ± 7% for the repeated K-fold-CV internal validation). Therefore, FTIR spectroscopy could be used as a fast, reliable, environmentally friendly and non-destructive olive cultivar-classification tool for monovarietal oils.en_EN
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and Project “Green- Health—Digital strategies in biological assets to improve well-being and promote green health” (Norte-01-0145-FEDER-000042) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. Nuno Rodrigues and Isabel P. Fernandes thank to National funding by FCT— Foundation for Science and Technology, P
dc.description.versioninfo:eu-repo/semantics/publishedVersionen_EN
dc.identifier.citationLamas, Sandra; Rodrigues, Nuno; Fernandes, Isabel P.; Barreiro, Maria F.; Pereira, José A.; Peres, António M. (2021). Fourier transform infrared spectroscopy-chemometric approach as a non-destructive olive cultivar tool for discriminating Portuguese monovarietal olive oils. European Food Research and Technology. ISSN 1438-2377. 247:10, p. 2473-2484en_EN
dc.identifier.doi10.1007/s00217-021-03809-8en_EN
dc.identifier.issn1438-2377
dc.identifier.urihttp://hdl.handle.net/10198/24292
dc.language.isoeng
dc.peerreviewedyesen_EN
dc.relationMountain Research Center
dc.subjectAuthenticityen_EN
dc.subjectData processingen_EN
dc.subjectFourier transform infrared spectroscopyen_EN
dc.subjectOlive oilen_EN
dc.subjectPortuguese cultivar discriminationen_EN
dc.titleFourier transform infrared spectroscopy-chemometric approach as a non-destructive olive cultivar tool for discriminating Portuguese monovarietal olive oilsen_EN
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMountain Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameLamas
person.familyNameRodrigues
person.familyNameFernandes
person.familyNameBarreiro
person.familyNamePereira
person.familyNamePeres
person.givenNameSandra
person.givenNameNuno
person.givenNameIsabel P.
person.givenNameFilomena
person.givenNameJosé Alberto
person.givenNameAntónio M.
person.identifier107333
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person.identifier.orcid0000-0002-4334-1636
person.identifier.orcid0000-0002-9305-0976
person.identifier.orcid0000-0002-0069-4503
person.identifier.orcid0000-0002-6844-333X
person.identifier.orcid0000-0002-2260-0600
person.identifier.orcid0000-0001-6595-9165
person.identifier.ridL-1552-2016
person.identifier.ridL-9802-2014
person.identifier.ridL-6798-2014
person.identifier.ridI-8470-2012
person.identifier.scopus-author-id57225883755
person.identifier.scopus-author-id55258560600
person.identifier.scopus-author-id26323585300
person.identifier.scopus-author-id57188719717
person.identifier.scopus-author-id57204366348
person.identifier.scopus-author-id7102331969
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccessen_EN
rcaap.typearticleen_EN
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