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Fatty-acid profiling vs UV-Visible fingerprints for geographical classification of Moroccan Argan oils

Kharbach, Mourad, Kamal, Rabie, Marmouzi, Ilias, Barra, Issam, Cherrah, Yahya, Alaoui, Katim, Heyden, Yvan Vander, Bouklouze, Abdelaziz
Food control 2019 v.95 pp. 95-105
chemometrics, discriminant analysis, least squares, oils, physicochemical properties, principal component analysis, provenance, seeds
Fatty-acid profiling vs UV-Visible fingerprinting in combination with chemometric tools were applied to classify edible Extra Virgin Argan Oils (EVAO) with protected geographic indication according to their geographical origins. Secondly, three EVAO categories classification were classified according to their extraction process (mechanical or traditional) and/or on the kernels (seeds) used for their preparation (roasted or unroasted). A total of 150 edible EVAO samples were collected during the harvest periods of 2012–2015, from five Moroccan Argan forests, i.e. Ait-Baha, Agadir, Essaouira, Tiznit, and Taroudant. A second set of 30 samples from the Taroudant region (harvest 2015) was used to classify in three EVAO categories according to extraction process/kernel type applied. Firstly, the EVAO quality is checked by determining physico-chemical parameters and the fatty-acid composition. Then, the UV-Visible spectra are recorded. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), were performed to classify the oils either according to their geographical origins or to their extraction process/kernel type. The results showed a highly significant discrimination of the five groups according to the region and of the three groups when considering the preparation.This study demonstrated the feasibility of UV-Visible fingerprinting (routine technique) for geographical classification or method preparation distinction.