1H NMR fingerprints of virgin olive oils (VOOs) from the Mediterranean basin (three harvests) were analyzed by principal component analysis, linear discriminant analysis (LDA), and partial least-squares discriminant analysis (PLS-DA) to determine their geographical origin at the national, regional, or PDO level. Further delta 13C and delta 2H measurements were performed by isotope ratio mass spectrometry (IRMS). LDA and PLS-DA achieved consistent results for the characterization of PDO Riviera Ligure VOOs. PLS-DA afforded the best model: for the Liguria class, 92% of the oils were correctly classified in the modeling step, and 88% of the oils were properly predicted in the external validation; for the non-Liguria class, 90 and 86% of hits were obtained, respectively. A stable and robust PLS-DA model was obtained to authenticate VOOs from Sicily: the recognition abilities were 98% for Sicilian oils and 89% for non-Sicilian ones, and the prediction abilities were 93 and 86%, respectively. More than 85% of the oils of both categories were properly predicted in the external validation. Greek and non-Greek VOOs were properly classified by PLS-DA: >90% of the samples were correctly predicted in the cross-validation and external validation. Stable isotopes provided complementary geographical information to the 1H NMR fingerprints of the VOOs.

ALONSO-SALCES Rosa;  MORENO-ROJAS Jose Manuel;  HOLLAND Margaret;  RENIERO Fabiano;  GUILLOU Claude;  HEBERGER Karoly; 

2011-01-19

AMER CHEMICAL SOC

JRC58393

0021-8561,   

https://publications.jrc.ec.europa.eu/repository/handle/JRC58393,   

10.1021/jf903989b,