A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication

作者：Bajoub Aadil; Medina Rodriguez Santiago; Ajal El Amine; Cuadros Rodriguez Luis; Paula Monasterio Romina; Vercammen Joeri; Fernandez Gutierrez Alberto; Carrasco Pancorbo Alegria^*

来源：Food Research International, 2018, 106: 233-242.

DOI：10.1016/j.foodres.2017.12.027

• Virgin olive oil
• Geographical indication labels
• Ion flow rube mass spectrometry
• Chemometrics
• Geographical origin authentication

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknes and Tyout (Morocco); and Priego de Cordoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H3O+, NO+ and O-2(+) as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases).

• 出版日期2018-4