Stepwise strategy based on 1H-NMR fingerprinting in combination with chemometrics to determine the content of vegetable oils in olive oil mixtures

•NMR fingerprinting & chemometrics to authenticate pure & legal blends of olive oil.•1H NMR & pattern recognition to detect adulteration olive oil with vegetable oils.•Stepwise strategy based on NMR spectral data and classification & regression models.•Olive oil traceability using de...

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Published in:Food chemistry 2022-01, Vol.366, p.130588-130588, Article 130588
Main Authors: Alonso-Salces, Rosa María, Berrueta, Luis Ángel, Quintanilla-Casas, Beatriz, Vichi, Stefania, Tres, 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
Format: Article
Language:English
Subjects:
Adulteration
Authentication
Decision tree
Multivariate data analysis
Nuclear magnetic resonance
Olive oil
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Summary:•NMR fingerprinting & chemometrics to authenticate pure & legal blends of olive oil.•1H NMR & pattern recognition to detect adulteration olive oil with vegetable oils.•Stepwise strategy based on NMR spectral data and classification & regression models.•Olive oil traceability using decision trees with classification & regression models.•Determination of the botanical nature and the percentage of each oil in a mixture. 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.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2021.130588