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Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach
dc.contributor.author | Sales Martínez, Carlos | |
dc.contributor.author | Portoles, Tania | |
dc.contributor.author | Johnsen, L. G. | |
dc.contributor.author | Danielsen, M. | |
dc.contributor.author | Beltran Arandes, Joaquin | |
dc.date.accessioned | 2018-09-11T07:15:30Z | |
dc.date.available | 2018-09-11T07:15:30Z | |
dc.date.issued | 2019-01-15 | |
dc.identifier.citation | SALES MARTÍNEZ, Carlos; PORTOLÉS NICOLAU, Tania; JOHNSEN, L. G.; DANIELSEN, M.; BELTRÁN ARANDES, Joaquim (2018). Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach. Food Chemistry, v. 271, p. 488-496 | ca_CA |
dc.identifier.uri | http://hdl.handle.net/10234/176025 | |
dc.description.abstract | The capabilities of dynamic headspace entrainment followed by thermal desorption in combination with gas chromatography (GC) coupled to single quadrupole mass spectrometry (MS) have been tested for the determi- nation of volatile components of olive oil. This technique has shown a great potential for olive oil quality classi fi cation by using an untargeted approach. The data processing strategy consisted of three di ff erent steps: component detection from GC – MS data using novel data treatment software PARADISe, a multivariate analysis using EZ-Info, and the creation of the statistical models. The great number of compounds determined enabled not only the development of a quality classi fi cation method as a complementary tool to the o ffi cial established method “ PANEL TEST ” but also a correlation between these compounds and di ff erent types of defect. Classi fi cation method was fi nally validated using blind samples. An accuracy of 85% in oil classi fi cation was obtained, with 100% of extra virgin samples correctly classi fi ed | ca_CA |
dc.format.extent | 25 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.relation.isPartOf | Food Chemistry (2019), v. 271 | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/CNE/1.0/ | * |
dc.subject | Dynamic headspace | ca_CA |
dc.subject | Olive oil | ca_CA |
dc.subject | GC–MS | ca_CA |
dc.subject | PARAFAC2 | ca_CA |
dc.subject | Foodomics | ca_CA |
dc.title | Olive oil quality classification and measurement of its organoleptic attributes by untargeted GC – MS and multivariate statistical-based approach | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1016/j.foodchem.2018.07.200 | |
dc.relation.projectID | 1) Generalitat Valenciana, Spain, as research group of excellence (PROMETEO II/ 2014/023); 2) Collaborative Research on Environment and Food-Safety (ISIC/2012/016); 3) University Jaume I, Spain (UJI-B2016-10); 4) Juan de la Cierva Incorporation Program from Ministry of Economy and Competitivenes, Spain (IJCI-2014-20588). | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.sciencedirect.com/science/article/pii/S0308814618313554 | ca_CA |
dc.contributor.funder | The investigation has been performed within the frame of scientific collaboration between the “ Ministerio de Agricultura, Alimentación y Medio Ambiente ” , the “ Consejería de Agricultura, Pesca y Desarrollo Rural de la Junta de Andalucía ” and the “ Interprofesional del Aceite de Oliva Español ” . | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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