dc.contributor.author | Alonso Salces, Rosa María | |
dc.contributor.author | Berrueta Simal, Luis Angel | |
dc.contributor.author | Quintanilla-Casas, Beatriz | |
dc.contributor.author | Vichi, Stefania | |
dc.contributor.author | Tres, Alba | |
dc.contributor.author | Collado González, María Isabel | |
dc.contributor.author | Asensio Regalado, Carlos | |
dc.contributor.author | Viacava, Gabriela E. | |
dc.contributor.author | Poliero, Aimará Ayelen | |
dc.contributor.author | Valli, Enrico | |
dc.contributor.author | Bendini, Alessandra | |
dc.contributor.author | Toschi, Tullia G. | |
dc.contributor.author | Martínez-Rivas, José Manuel | |
dc.contributor.author | Moreda, Wenceslao | |
dc.contributor.author | Gallo Hermosa, Blanca | |
dc.date.accessioned | 2023-12-20T12:22:21Z | |
dc.date.available | 2023-12-20T12:22:21Z | |
dc.date.issued | 2022-01-01 | |
dc.identifier.citation | Food Chemistry 366 : (2022) // 130588 | es_ES |
dc.identifier.issn | 0308-8146 | |
dc.identifier.uri | http://hdl.handle.net/10810/63444 | |
dc.description.abstract | 1H NMR fingerprinting of edible oils and a set of multivariate classification and regression models organised in a decision tree is proposed as a stepwise strategy to assure the authenticity and traceability of olive oils and their declared blends with other vegetable oils (VOs). Oils of the ‘virgin olive oil’ and ‘olive oil’ categories and their mixtures with the most common VOs, i.e. sunflower, high oleic sunflower, hazelnut, avocado, soybean, corn, refined palm olein and desterolized high oleic sunflower oils, were studied. Partial least squares (PLS) discriminant analysis provided stable and robust binary classification models to identify the olive oil type and the VO in the blend. PLS regression afforded models with excellent precisions and acceptable accuracies to determine the percentage of VO in the mixture. The satisfactory performance of this approach, tested with blind samples, confirm its potential to support regulations and control bodies. | es_ES |
dc.description.sponsorship | This work was developed in the framework of the project OLEUM “Advanced solutions for assuring authenticity and quality of olive oil at global scale” funded by the European Commission within the Horizon 2020 Programme (2014–2020), grant agreement No. 635690; and the project AUTENFOOD funded by ACCIÓ-Generalitat de Catalunya and the European Union through the Programa Operatiu FEDER Catalunya 2014-2020 (Ref COMRDI-15-1-0035). The information contained in this article reflects the authors’ views; the European Commission is not liable for any use of the information contained herein. The authors would like to thank all producers that supplied the olive oils, virgin olive oils and vegetable oils for this study, and the technical and staff support provided by SGIker (UPV/EHU, MICINN, GV/EJ, ESF). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/635690 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | |
dc.subject | olive oil | es_ES |
dc.subject | nuclear magnetic resonance | es_ES |
dc.subject | multivariate data analysis | es_ES |
dc.subject | decision tree | es_ES |
dc.subject | adulteration | es_ES |
dc.subject | authentication | es_ES |
dc.title | Stepwise strategy based on 1H-NMR fingerprinting in combination with chemometrics to determine the content of vegetable oils in olive oil mixtures | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | CC BY-NC-ND 4.0 | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.foodchem.2021.130588 | es_ES |
dc.identifier.doi | 10.1016/j.foodchem.2021.130588 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Química analítica | es_ES |
dc.departamentoeu | Kimika analitikoa | es_ES |