Discrimination and classification of olive tree varieties and cultivation zones by biophenol contents.

The peak areas from a high-performance liquid chromatography-diode array (HPLC-DAD) analysis of biophenols extracted from olive leaves have been used as chemotaxonomic markers to construct chemometric models in order to discriminate and classify (1) 13 varieties of Olea europaea olive trees, namely, Alameño, Arbequina, Azulillo, Chorna, Hojiblanca, Lechín, Manzanillo, Negrillo, Nevadillo, Ocal, Pierra, Sevillano, and Tempranillo, from the same cultivation zone and (2) Arbequina samples from six different geoghaphical origins, namely, Córdoba, Mallorca (north and south), Ciudad Real, Lleida, and Navarra. Models based on principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for discrimination between samples as a function of the tree varieties and cultivation zone, whereas K nearest neighbors (KNN) and soft independent modeling of class analogy (SIMCA) models were generated to classify the samples used to validate the models into one of the groups previously established by PCA and HCA. KNN classified correctly 93 and 92% of the samples into the variety and cultivation zone, respectively; meanwhile, the SIMCA models predicted 85 and 92%, respectively.