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Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue

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dc.contributor.authorMarx, Ítala
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorDias, L.G.
dc.contributor.authorVeloso, Ana C.A.
dc.contributor.authorPereira, J.A.
dc.contributor.authorDrunkler, Deisy A.
dc.contributor.authorPeres, António M.
dc.date.accessioned2018-01-25T10:00:00Z
dc.date.accessioned2018-01-30T15:00:18Z
dc.date.available2018-01-25T10:00:00Z
dc.date.available2018-01-30T15:00:18Z
dc.date.issued2017
dc.description.abstractTable olives are prone to the appearance of sensory defects that decrease their quality and in some cases result in olives unsuitable for consumption. The evaluation of the type and intensity of the sensory negative attributes of table olives is recommended by the International Olive Council, although not being legally required for commercialization. However, the accomplishment of this task requires the training and implementation of sensory panels according to strict directives, turning out in a time-consuming and expensive procedure that involves a degree of subjectivity. In this work, an electronic tongue is proposed as a taste sensor device for evaluating the intensity of sensory defects of table olives. The potentiometric signal profiles gathered allowed establishing multiple linear regression models, based on the most informative subsets of signals (from 24 to 29 recorded during the analysis of olive aqueous pastes and brine solutions) selected using a simulated annealing meta-heuristic algorithm. The models enabled the prediction of the median intensities (R 2 = 0.942 and RMSE = 0.356, for leave-one-out or repeated K-fold cross-validation procedures) of butyric, musty, putrid, winey-vinegary, and zapateria negative sensations being, in general, the predicted intensities within the range of intensities perceived by the sensory panel. Indeed, based on the predicted mean intensities of the sensory defects, the electrochemical-chemometric approach developed could correctly classify 86.4% of the table olive samples according to their trade category based on a sensory panel evaluation and following the International Olive Council regulations (i.e., extra, 1st choice, 2nd choice, and olives that may not be sold as table olives). So, the satisfactory overall predictions achieved demonstrate that the electronic tongue could be a complementary tool for assessing table olive defects, reducing the effort of trained panelists and minimizing the risk of subjective evaluations.pt_PT
dc.description.sponsorshipThis work was financially supported by Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRE-LCM, by Project UID/QUI/00616/2013—CQ-VR, and UID/AGR/00690/ 2013—CIMO, all funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through Fundação para a Ciência e a Tecnologia (FCT), Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN, and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMarx, Ítala; Rodrigues, Nuno; Dias, L.G.; Veloso, Ana C.A.; Pereira, José A.; Drunkler, Deisy A.; Peres, António M. (2017). Assessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongue. Food and Bioprocess Technology. ISSN 1935-5130. 10, p. 1310-1323en_EN
dc.identifier.doi10.1007/s11947-017-1902-7pt_PT
dc.identifier.issn1935-5130
dc.identifier.urihttp://hdl.handle.net/10198/15286
dc.language.isoeng
dc.peerreviewedyespt_PT
dc.subjectElectronic tongueen_EN
dc.subjectMultivariate linear regression modelsen_EN
dc.subjectSensory defects intensityen_EN
dc.subjectSimulated annealing algorithmen_EN
dc.subjectTable olivesen_EN
dc.titleAssessment of Table Olives’ Organoleptic Defect Intensities Based on the Potentiometric Fingerprint Recorded by an Electronic Tongueen_EN
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FBIO%2F04469%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FQUI%2F00616%2F2013/PT
oaire.fundingStream5876
oaire.fundingStream5876
person.familyNameMarx
person.familyNameRodrigues
person.familyNameDias
person.familyNamePereira
person.familyNamePeres
person.givenNameÍtala
person.givenNameNuno
person.givenNameLuís G.
person.givenNameJosé Alberto
person.givenNameAntónio M.
person.identifier1676851
person.identifier107333
person.identifier.ciencia-id2717-C420-DEAE
person.identifier.ciencia-idF41D-B424-5F78
person.identifier.ciencia-id2F11-9092-FAAF
person.identifier.ciencia-id611F-80B2-A7C1
person.identifier.ciencia-idCF16-5443-F420
person.identifier.orcid0000-0002-7049-2114
person.identifier.orcid0000-0002-9305-0976
person.identifier.orcid0000-0002-1210-4259
person.identifier.orcid0000-0002-2260-0600
person.identifier.orcid0000-0001-6595-9165
person.identifier.ridGLV-5485-2022
person.identifier.ridL-6798-2014
person.identifier.ridI-8470-2012
person.identifier.scopus-author-id57191503603
person.identifier.scopus-author-id55258560600
person.identifier.scopus-author-id23569169900
person.identifier.scopus-author-id57204366348
person.identifier.scopus-author-id7102331969
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccessen_EN
rcaap.typearticlept_PT
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