Chemometric detection and quantification of virgin olive oil adulteration using GC-FID fatty acid profiling

Abstract

Virgin olive oil (VOO) authentication is crucial for protecting geographical designations and consumer confidence, particularly for emerging regional varieties. This study presents a comprehensive authentication framework for Moroccan Picholine VOO using gas chromatography-flame ionization detection (GC-FID) fatty acid profiling combined with chemometric modelling. Following quality screening of 107 Picholine VOO samples collected across the Tanger-Tetouan-Al Hoceima region (2024 harvest), three representative samples with distinct compositional profiles were selected as matrix references for systematic adulteration testing. Binary mixtures with soybean and sunflower oils were prepared at 10 adulteration levels (5–90% w/w), generating a 63-sample dataset. Physicochemical parameters (acidity, peroxide value, UV indices) and complete fatty acid profiles were determined according to IOC standards. Five chemometric approaches were systematically compared: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and support vector regression (SVR). For discrimination between the two adulterant types (soybean vs. sunflower), the SVM model achieved 100% accuracy on the held-out test set; the authentic class could not be evaluated in this test set owing to the limited number of pure samples (see Limitations). The lowest experimentally verified adulteration level was 5% (w/w). For quantitative analysis, SVR models demonstrated excellent predictive capability with R² values up to 0.998 on an independent test set and root mean square errors below 1.5% for the best-performing model and root mean square errors below 1.5% for both adulterant types. This study provides the first regional authentication reference for northern Moroccan Picholine and validates a cost-effective GC-FID methodology applicable to routine quality control in emerging olive-producing regions.