Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/40249
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Campo DC | Valor | Idioma |
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dc.contributor.author | Dias, Luís G. | por |
dc.contributor.author | Rodrigues, Nuno | por |
dc.contributor.author | Veloso, Ana C. A. | por |
dc.contributor.author | Pereira, José A. | por |
dc.contributor.author | Peres, António M. | por |
dc.date.accessioned | 2016-02-12T14:56:48Z | - |
dc.date.available | 2016-02-12T14:56:48Z | - |
dc.date.issued | 2016-02 | - |
dc.identifier.citation | Dias, Luís G.; Rodrigues, Nuno; Veloso, Ana C. A.; Pereira, José A.; Peres, António M., Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue. European Food Research and Technology, 242(2), 259-270, 2016 | por |
dc.identifier.issn | 1438-2377 | por |
dc.identifier.uri | https://hdl.handle.net/1822/40249 | - |
dc.description.abstract | Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination. | por |
dc.description.sponsorship | This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundacao para a Ciencia e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC-Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal. | por |
dc.language.iso | eng | por |
dc.publisher | Springer Verlag | por |
dc.rights | openAccess | por |
dc.subject | Single-cultivar extra-virgin olive oil | por |
dc.subject | Sensory analysis | por |
dc.subject | Potentiometric electronic tongue | por |
dc.subject | Linear multivariate methods | por |
dc.subject | Simulated annealing algorithm | por |
dc.title | Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://www.springer.com/food+science/journal/217 | por |
dc.comments | CEB22361 | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 259 | por |
oaire.citationEndPage | 270 | por |
oaire.citationIssue | 2 | por |
oaire.citationConferencePlace | Germany | - |
oaire.citationTitle | European Food Research and Technology | por |
oaire.citationVolume | 242 | por |
dc.date.updated | 2016-01-24T16:08:52Z | - |
dc.identifier.eissn | 1438-2385 | - |
dc.identifier.doi | 10.1007/s00217-015-2537-4 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | European Food Research and Technology | por |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document_22361_1.pdf | 629,97 kB | Adobe PDF | Ver/Abrir |