Geographical authentication of virgin olive oil by GC-MS sesquiterpene hydrocarbon fingerprint: Scaling down to the verification of PDO compliance

Classification of Black Mahlab seeds (Monechma ciliatum) using GC-MS and FT-NIR and simultaneous prediction of their major volatile compounds using chemometrics

The identification of geographical origin is an important factor in assessing the quality of aromatic and medicinal seeds such as Black Mahlab (Monechma ciliatum). However, at present, there are no studies concerning Black Mahlab Seeds (BMSs). To identify the geographical origin of BMSs, we have used gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-NIR) combined with chemometrics. Chemometrics analysis showed that FT-NIR and GC-MS can be used to discriminate the geographical origin of BMSs. FT-NIR coupled with the partial least squares regression (PLSR) was applied to develop the calibration models. The calibration models had a coefficient of determination (R_c²) of 0.82 for coumarin and 0.81 for methyl salicylate. The prediction model (R_p²) values ranged from 0.83 for coumarin to 0.77 for methyl salicylate. Overall, the chemometrics presented correct classification, and PLSR accurately predicted the volatiles, with an RMSEP range of 0.9 to 0.16 for the two volatiles targeted.

Combining different biomarkers to distinguish Chemlali virgin olive oils from different geographical areas of Tunisia

BACKGROUND

Despite their high potential, Tunisian virgin olive oils (VOOs) are mainly exported in bulk or blended with VOOs of other origin, hindering their international market placement. To face this situation, their valorization is needed by highlighting their unique features and by developing tools to guarantee their geographical authenticity. Compositional features of Chemlali VOOs produced in three Tunisian regions were assessed to identify suitable authenticity markers.

RESULTS

Quality indices ensured the quality of the VOOs studied. Volatile compounds, total phenols, fatty acid (FA) and chlorophylls are significantly influenced by the region of origin, which was justified by the differences found in soil and climatic conditions of the three geographical regions. To explore the capabilities of these markers for the geographical authentication of Tunisian Chemlali VOOs, classification models based on partial least squares-discriminant analysis (PLS-DA) were developed by grouping the minimum number of variables allowing the highest discrimination power, minimizing in this way the analytical procedure. The PLS-DA authentication model based on combining volatile compounds with FA or with total phenols achieved a correct classification of 95.7% of the VOOs according to their origin, as assessed by 10%-out cross-validation. Sidi Bouzid Chemlali VOOs achieved 100% of correct classification, while the misclassification between Sfax and Enfidha ones did not exceed 10%.

CONCLUSIONS

These results allowed to establish the most promising and affordable combination of markers for the geographical authentication of Tunisian Chemlali VOOs from distinct production regions and provide the basis to further develop authentication models based on wider datasets. © 2023 Society of Chemical Industry.