Publicação
An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions
| Resumo: | The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils’ geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 < R2 < 0.998 and 0.40 < RMSE < 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles. |
|---|---|
| Autores principais: | Rodrigues, Nuno |
| Outros Autores: | Ferreiro, Nuno Manuel; Veloso, Ana C.A.; Pereira, J.A.; Peres, António M. |
| Assunto: | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867172976463446016 |
|---|---|
| author | Rodrigues, Nuno |
| author2 | Ferreiro, Nuno Manuel Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
| author2_role | author author author author |
| author_facet | Rodrigues, Nuno Ferreiro, Nuno Manuel Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Rodrigues, Nuno\",\"Person.identifier.orcid\":\"0000-0002-9305-0976\"},{\"Person.name\":\"Ferreiro, Nuno Manuel\"},{\"Person.name\":\"Veloso, Ana C.A.\"},{\"Person.name\":\"Pereira, J.A.\",\"Person.identifier.orcid\":\"0000-0002-2260-0600\"},{\"Person.name\":\"Peres, António M.\",\"Person.identifier.orcid\":\"0000-0001-6595-9165\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Rodrigues, Nuno Ferreiro, Nuno Manuel Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
| datacite.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-02-07T15:56:52Z |
| datacite.date.embargoed.fl_str_mv | 2023-02-07T15:56:52Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| datacite.titles.title.fl_str_mv | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Rodrigues, Nuno Ferreiro, Nuno Manuel Veloso, Ana C.A. Pereira, J.A. Peres, António M. |
| dc.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-02-07T15:56:52Z |
| dc.date.embargoed.fl_str_mv | 2023-02-07T15:56:52Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/26780 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| dc.title.fl_str_mv | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils’ geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 < R2 < 0.998 and 0.40 < RMSE < 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/f8c5973e-0ec5-48aa-8dd2-1a2a240cfc4e/download |
| funding.funder.alternateName_str_mv | FCT FCT FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | 6817 - DCRRNI ID 6817 - DCRRNI ID 6817 - DCRRNI ID |
| id | ipb_2eeb2fa5cac7201528696ec68a28cf7a |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/26780 |
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| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/26780 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Rodrigues, Nuno Rodrigues, Nuno https://www.ciencia-id.pt/F41D-B424-5F78 F41D-B424-5F78 http://orcid.org/0000-0002-9305-0976 0000-0002-9305-0976 Ferreiro, Nuno Manuel Veloso, Ana C.A. Pereira, J.A. Pereira, J.A. https://www.ciencia-id.pt/611F-80B2-A7C1 611F-80B2-A7C1 http://orcid.org/0000-0002-2260-0600 0000-0002-2260-0600 Peres, António M. Peres, António M. https://www.ciencia-id.pt/CF16-5443-F420 CF16-5443-F420 http://orcid.org/0000-0001-6595-9165 0000-0001-6595-9165 |
| publishDate | 2022 |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engpt_PTThe geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils’ geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 < R2 < 0.998 and 0.40 < RMSE < 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.application/pdfpt_PTAn electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regionsPersonalRodrigues, NunoDSpacehttp://dspace.org/items/00739d63-995d-4b1f-97d0-03d24c7cf0fdDSpacehttp://dspace.org/items/00739d63-995d-4b1f-97d0-03d24c7cf0fdRodriguesNunoCiência IDhttps://www.ciencia-id.ptF41D-B424-5F78ORCIDhttp://orcid.org0000-0002-9305-0976Scopus Author IDhttps://www.scopus.com55258560600Ferreiro, Nuno ManuelVeloso, Ana C.A.PersonalPereira, J.A.DSpacehttp://dspace.org/items/7932162e-a2da-4913-b00d-17babbe51857DSpacehttp://dspace.org/items/7932162e-a2da-4913-b00d-17babbe51857PereiraJosé AlbertoCiência IDhttps://www.ciencia-id.pt611F-80B2-A7C1ORCIDhttp://orcid.org0000-0002-2260-0600Researcher IDhttps://www.researcherid.comL-6798-2014Scopus Author IDhttps://www.scopus.com57204366348PersonalPeres, António M.DSpacehttp://dspace.org/items/7d93be47-8dc4-4413-9304-5b978773d3bbDSpacehttp://dspace.org/items/7d93be47-8dc4-4413-9304-5b978773d3bbPeresAntónio M.Ciência IDhttps://www.ciencia-id.ptCF16-5443-F420ORCIDhttp://orcid.org0000-0001-6595-9165Researcher IDhttps://www.researcherid.comI-8470-2012Scopus Author IDhttps://www.scopus.com7102331969HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISSNIsPartOf1424-3210DOIIsPartOf10.3390/s222496512023-02-07T15:56:52Z20222022-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/26780http://purl.org/coar/access_right/c_abf2open accessEVOO qualitySensory analysisOxidative stabilityMetal oxide semiconductor sensorsMultivariate qualitative-quantitative analysisResistance electrical signalsFeature extraction parameters2033790 bytesFundação para a Ciência e a TecnologiaMountain Research Center6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaMountain Research Center6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaCentre of Biological Engineering of the University of Minho6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal article2022http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/f8c5973e-0ec5-48aa-8dd2-1a2a240cfc4e/downloadSensors22249651 |
| spellingShingle | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions Rodrigues, Nuno EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| status | SINGLETON |
| subject.fl_str_mv | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| title | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| title_full | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| title_fullStr | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| title_full_unstemmed | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| title_short | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| title_sort | An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions |
| topic | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| topic_facet | EVOO quality Sensory analysis Oxidative stability Metal oxide semiconductor sensors Multivariate qualitative-quantitative analysis Resistance electrical signals Feature extraction parameters |
| url | http://hdl.handle.net/10198/26780 |
| visible | 1 |