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dc.contributor.authorNasr, Emna G.
dc.contributor.authorEpova, Ekaterina N.
dc.contributor.authorDe Diego Rodríguez, Alberto ORCID
dc.contributor.authorSouissi, Radhia
dc.contributor.authorHammami, Mohamed
dc.contributor.authorAbderrazak, Houyem
dc.contributor.authorF. X. Donard, Olivier
dc.date.accessioned2022-01-13T11:21:02Z
dc.date.available2022-01-13T11:21:02Z
dc.date.issued2021-12-29
dc.identifier.citationFoods 11(1) : (2022) // Article ID 82es_ES
dc.identifier.issn2304-8158
dc.identifier.urihttp://hdl.handle.net/10810/54935
dc.description.abstractThe aim of this study was to investigate the levels of trace elements in olive oils from different locations and their use for geographical authentication. Concentrations of seventeen elements were determined in a total of 42 olive oils from Tunisia, Spain (Basque country), and southern France, and in nine soil samples from Tunisia by quadrupole inductively plasma mass spectrometry. The compilation of appropriate techniques integrated into the analytical procedure achieved a precision (RSD) between 2% and 15% and low limits of detection (between 0.0002 and 0.313 µg kg−1). The accuracy of the analytical method applied for olive oil analysis was evaluated using SRM NIST 2387 Peanut butter. The recoveries obtained after microwave-assisted digestion for the certified elements ranged between 86% and 102%. Concentrations of non-certified elements (V, Cr, Co, Ni, Ba, Rb, Sr, Cd, Pb, and As) were presented. The use of Pearson correlation applied on paired Tunisian oil/soil samples has shown that several elements (Mg, Mn, Ni, and Sr) were significantly correlated. The multivariate statistics using principal component analysis have successfully discriminated against three studied origins. The most significant variables were the elemental concentrations of Cu, Cr, Fe, Mn, Sr, V, and Zn. This study shows the potential of applying trace elements profiles for olive oil geographical discrimination.es_ES
dc.description.sponsorshipThis research was funded by European Project TunTwin from the Horizon 2020 Framework program of the European Union under grant No. 952306. It was also funded by the French ANR EquiPex MARSS project with a contribution of the METROFOOD ESFRI project. This work was partially supported by the Euskadi/Nouvelle Aquitaine/Navarra Eurorregion through the research project ISOTOPO (with agreement no. 2020/3). The financial support of a Ph.D. grant for Emna G. Nasr has been provided by the “Excellence Eiffel” scholarship of Campus France, the European project “TunTwin” and the scholarship “bourse d’alternance” of University Tunis El Manar, Ministry of Higher Education and Scientific Research in Tunisia.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/952306es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectolive oiles_ES
dc.subjectinductively plasma mass spectrometryes_ES
dc.subjectsoiles_ES
dc.subjecttrace elementses_ES
dc.subjectprincipal component analysises_ES
dc.subjectgeographical discriminationes_ES
dc.titleTrace Elements Analysis of Tunisian and European Extra Virgin Olive Oils by ICP-MS and Chemometrics for Geographical Discriminationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2022-01-10T14:38:01Z
dc.rights.holder2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2304-8158/11/1/82/htmes_ES
dc.identifier.doi10.3390/foods11010082
dc.contributor.funderEuropean Commission
dc.departamentoesQuímica analítica
dc.departamentoeuKimika analitikoa


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2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).