Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/46350

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dc.contributor.authorMarx, Ítala M. G.por
dc.contributor.authorRodrigues, Nunopor
dc.contributor.authorDias, Luís G.por
dc.contributor.authorVeloso, Ana C. A.por
dc.contributor.authorPereira, José A.por
dc.contributor.authorDrunkler, Deisy A.por
dc.contributor.authorPeres, António M.por
dc.date.accessioned2017-08-05T15:29:01Z-
dc.date.available2017-08-05T15:29:01Z-
dc.date.issued2017-07-
dc.identifier.citationMarx, Ítala M. G.; Rodrigues, Nuno; Dias, Luís G.; Veloso, Ana C. A.; Pereira, José A.; Drunkler, Deisy A.; Peres, António M., Assessment of table olives' organoleptic defect intensities based on the potentiometric fingerprint recorded by an electronic tongue. Food and Bioprocess Technology, 10(7), 1310-1323, 2017por
dc.identifier.issn1935-5130por
dc.identifier.urihttp://hdl.handle.net/1822/46350-
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 (R2 ≥ 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.por
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).por
dc.language.isoengpor
dc.publisherSpringer Naturepor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147416/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147337/PTpor
dc.relationSFRH/BD/104038/2014por
dc.rightsopenAccesspor
dc.subjectTable olivespor
dc.subjectSensory defects intensitypor
dc.subjectElectronic tonguepor
dc.subjectMultivariate linear regression modelspor
dc.subjectSimulated annealing algorithmpor
dc.titleAssessment of table olives' organoleptic defect intensities based on the potentiometric fingerprint recorded by an electronic tonguepor
dc.typearticle-
dc.peerreviewedyespor
dc.relation.publisherversionhttp://www.springer.com/food+science/journal/11947por
dc.commentsCEB46740por
degois.publication.firstPage1310por
degois.publication.lastPage1323por
degois.publication.issue7por
degois.publication.locationUnited States-
degois.publication.volume10por
dc.date.updated2017-08-03T11:08:39Z-
dc.identifier.essn1935-5149por
dc.identifier.doi10.1007/s11947-017-1902-7por
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
sdum.journalFood and Bioprocess Technologypor
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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