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Application of a lab-made electronic nose as a tool to assess extra virgin olive oil sensory category

2024Conference object Open access
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datacite.subject.fosCiências Agrárias::Biotecnologia Agrária e Alimentar
datacite.subject.sdg02:Erradicar a Fome
dc.contributor.authorFerreiro, Nuno Manuel
dc.contributor.authorVeloso, Ana C.A.
dc.contributor.authorRodrigues, Nuno
dc.contributor.authorPereira, José Alberto
dc.contributor.authorPeres, António M.
dc.date.accessioned2025-10-31T11:28:22Z
dc.date.available2025-10-31T11:28:22Z
dc.date.issued2024
dc.description.abstractPremium extra virgin olive oils are usually subjected to national and international contests aiming to promote their competitiveness and internationalization capacity. Olive oils were assessed by a sensory expert panel and initially split according to the perceived intensity of the fruitiness sensation into four categories, namely ripe (RF), green delicate (GD), green medium (GM), and green robust (GR) fruitiness.1 However, even for trained panelists, the assessment comprises a subjectivity degree, and the number of oils that can be evaluated per day is limited. In this sense, the use of electronic sensing devices can be helpful as pre-assessment tools, which may allow reducing the initial number of oils to be evaluated. Thus, a lab-made electronic nose (E-nose) comprising nine commercial metal oxide semiconductor (MOS) sensors, previously developed by the research team,2 was applied (Figure 1) aiming to verify its suitability for this purpose. In total, 59 olive oils were included in this study, which were previously classified by an expert sensory panel in a national contest: 20 oils as RF, 15 as GD, 17 as GM and 7 as GR fruitiness. For the E-nose analysis, 0.5 mL of each olive oil was inserted into a 25 mL glass vial and placed in the sampling chamber at 28 ºC (temperature recommended by the International Olive Council for sensory analysis of olive oils) for 13-min, allowing to generate a volatile fraction representative of the sample. After a cleaning step of the sensors’ surfaces using an air flow, the gas headspace from each sample was directed into the detection chamber, where it interacted with the MOS sensors for 2.5 min. The resistance signals of each of the nine MOS sensors were recorded by a data logger at 4 sec intervals being then treated taking into account seven distinct feature extraction methods: the last response point (LP), the integral of the response curve (INT), the maximum response point (MAX), the minimum response point (MIN), the sum of the response curve (SUM), and the mean of the response curve (MEAN).3 The results showed that the E-nose feature extracted data could be used to satisfactorily discriminate, based on a linear discriminant analysis (LDA) coupled with a simulated annealing (SA) algorithm, the olive oils according to sensory category groups with a sensitivity of 100% for training (Figure 2a) and 73% for the leave-one-out cross-validation (LOO-CV) procedure. The lower sensitivity achieved for the internal validation was mainly due to misclassification between GD and GM. Indeed, the classification performance of the E-nose-LDA-SA could be enhanced if only three groups were considered: RF, GD+GM and GI fruitiness. In this case the E-nose could correctly classify 100% of the oils for training (Figure 2b) and 92% for LOO-CV. In conclusion, the E-nose could be effectively applied as a rapid, cost-effective, and non-invasive tool for olive oil sensory classification.eng
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES (PIDDAC) to CIMO (UIDB/00690/2020, https://doi.org/10.54499/UIDB/00690/2020; and UIDP/00690/2020, https://doi.org/10.54499/UIDP/00690/2020) CEB (UIDB/04469/2020) units as well as to the Associate Laboratory SusTEC (LA/P/0007/2020). National funding by FCT- Foundation for Science and Technology, through the institutional scientific employment program-contract with Nuno Rodrigues. Nuno Ferreiro acknowledges the Ph.D. research grant (2022.10072.BD) provided by FCT.
dc.identifier.citationFerreiro, Nuno Manuel; Veloso, Ana C.A.; Rodrigues, Nuno; Pereira, José Alberto; Peres, António M. (2024). Application of a lab-made electronic nose as a tool to assess extra virgin olive oil sensory category. In XVII Encontro Nacional Química dos Alimentos. Vila Real. ISBN 978-989-8124-45-6
dc.identifier.isbn978-989-8124-45-6
dc.identifier.urihttp://hdl.handle.net/10198/34903
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSociedade Portuguesa de Química
dc.relationMountain Research Center
dc.relationCentre of Biological Engineering of the University of Minho
dc.relationExtra virgin olive oil shelf-life prediction based on an integrated approach from farm to fork
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relationMountain Research Center
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectExtra virgin olive oil
dc.titleApplication of a lab-made electronic nose as a tool to assess extra virgin olive oil sensory categorypor
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleMountain Research Center
oaire.awardTitleCentre of Biological Engineering of the University of Minho
oaire.awardTitleExtra virgin olive oil shelf-life prediction based on an integrated approach from farm to fork
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardTitleMountain Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04469%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/2022.10072.BD/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00690%2F2020/PT
oaire.citation.conferenceDate2024
oaire.citation.conferencePlaceVila Real
oaire.citation.endPage257
oaire.citation.startPage257
oaire.citation.titleXVII Encontro Nacional Química dos Alimentos
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamPOR_NORTE
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRodrigues
person.familyNamePereira
person.familyNamePeres
person.givenNameNuno
person.givenNameJosé Alberto
person.givenNameAntónio M.
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person.identifier.orcid0000-0002-9305-0976
person.identifier.orcid0000-0002-2260-0600
person.identifier.orcid0000-0001-6595-9165
person.identifier.ridL-6798-2014
person.identifier.ridI-8470-2012
person.identifier.scopus-author-id55258560600
person.identifier.scopus-author-id57204366348
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project.funder.nameFundação para a Ciência e a Tecnologia
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