NMR-based metabolomics for olive oil cultivar classification: A comparison with standard targeted analysis of fatty acids and triglycerides

Chromatographic techniques such as GC and HPLC are traditionally used for the analysis and classification of olive oil, while NMR is another powerful technique. In this paper we used NMR for the first time to classify olive oil produced by four cultivars, namely ‘Arbequina’, ‘Arbosana’, ‘Koroneiki’, and ‘Sikitita’, planted in super-high-density frames in California, United States. We compared the results with the targeted analysis of fatty acids and triglycerides obtained by GC-FID and UHPLC-CAD, respectively. All three techniques were able to distinguish between cultivars, with fatty acids from GC-FID generating the best models. GC-FID require time-consuming sample preparation; both GC-FID and UHPLC-CAD require lengthy analysis time and protocols for different classes of compounds, while NMR is rapid and able to conduct a simultaneous broad-spectrum analysis of compounds, which led to the discovery of more biomarkers. In addition, NMR was in a good agreement with GC-FID for the determination of fatty acids, as found by Bland-Altman analysis, although in several cases it was not able to distinguish among individual fatty acids.