Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/12837 |
Resumo: | Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactory–gustatory 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. |
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Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongueSingle-cultivar extra-virgin olive oilSensory analysisPotentiometric electronic tongueLinear multivariate methodsSimulated annealing algorithmOlive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactory–gustatory 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.Biblioteca Digital do IPBDias, L.G.Rodrigues, NunoVeloso, Ana C.A.Pereira, J.A.Peres, António M.2016-03-29T16:59:06Z20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/12837engDias, L.G.; Rodrigues, Nuno; Veloso, Ana C.A.; Pereira, J.A.; Peres, António M. (2016). Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue. European Food Research and Technology. ISSN 1438-2377. 242:2, p. 259–2701438-237710.1007/s00217-015-2537-4info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-21T10:29:58Zoai:bibliotecadigital.ipb.pt:10198/12837Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:03:00.991521Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
title |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
spellingShingle |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue Dias, L.G. Single-cultivar extra-virgin olive oil Sensory analysis Potentiometric electronic tongue Linear multivariate methods Simulated annealing algorithm |
title_short |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
title_full |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
title_fullStr |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
title_full_unstemmed |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
title_sort |
Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue |
author |
Dias, L.G. |
author_facet |
Dias, L.G. Rodrigues, Nuno Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
author_role |
author |
author2 |
Rodrigues, Nuno Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Dias, L.G. Rodrigues, Nuno Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
dc.subject.por.fl_str_mv |
Single-cultivar extra-virgin olive oil Sensory analysis Potentiometric electronic tongue Linear multivariate methods Simulated annealing algorithm |
topic |
Single-cultivar extra-virgin olive oil Sensory analysis Potentiometric electronic tongue Linear multivariate methods Simulated annealing algorithm |
description |
Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactory–gustatory 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. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-03-29T16:59:06Z 2016 2016-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10198/12837 |
url |
http://hdl.handle.net/10198/12837 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Dias, L.G.; Rodrigues, Nuno; Veloso, Ana C.A.; Pereira, J.A.; Peres, António M. (2016). Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue. European Food Research and Technology. ISSN 1438-2377. 242:2, p. 259–270 1438-2377 10.1007/s00217-015-2537-4 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799135272177238016 |