Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/180440
Title: | Stepwise strategy based on 1H-NMR fingerprinting in combination with chemometrics to determine the content of vegetable oils in olive oil mixtures |
Author: | Alonso-Salces, Rosa M. Berrueta, Luis Ángel Quintanilla-Casas, Beatriz Vichi, S. (Stefania) Tres Oliver, Alba Collado, María Isabel Asensio-Regalado, Carlos Viacava, Gabriela Elena Poliero, Aimará Ayelen Valli, Enrico Bendini, Alessandra Gallina Toschi, Tullia Martínez-Rivas, José Manuel Moreda, Wenceslao Gallo, Blanca |
Keywords: | Oli d'oliva Antropometria Química dels aliments Olive oil Anthropometry Food composition |
Issue Date: | 1-Jan-2022 |
Publisher: | Elsevier B.V. |
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. Keywords: Adulteration; Authentication; Decision tree; Multivariate data analysis; Nuclear magnetic resonance; Olive oil. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1016/j.foodchem.2021.130588 |
It is part of: | Food Chemistry, 2022, vol. 366, p. 130588 |
URI: | http://hdl.handle.net/2445/180440 |
Related resource: | https://doi.org/10.1016/j.foodchem.2021.130588 |
ISSN: | 0308-8146 |
Appears in Collections: | Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia) Publicacions de projectes de recerca finançats per la UE |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
713964.pdf | 3.27 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License