Purpose On 2009 the European Union (EU) Member States agreed to require origin labeling for virgin and extra virgin olive oils (EC Regulation 182/2009) to defend consumers need about true characteristics and origin. This Regulation, together with the well established laws regarding denominations and protected indications of origin (PDO PGI and TSG), has led to a new olive oil market where geographic origin labels are a big market competitive advantage. The extra virgin olive oil is also susceptible to several kind of adulterations, involving its blending with oils of scarce quality or of different botanical variety. In this context, quality markers of extra virgin olive oil have been identified and whose determination has become mandatory for its marketing. The purpose of the present work is to highlight the possible differences in mandatory chemical parameters and antioxidant properties among oil samples of different geographical origin. Both commercial and artisanal samples were analyzed and compared.
Design/methodology/approach. Fifty-five samples of extra virgin olive oil of known origin were analyzed for peroxide number, ΔK, free acidity percentage, total polyphenols and antioxidant capacity (by DPPH test). The results were then processed by multivariate statistical techniques such as ANOVA, Principal Component Analysis and Linea Discriminant Analysis.
Findings. All the mandatory parameters for all the samples analyzed were in the range of the legal limits, indicating an overall quality. Moreover, the samples were clearly discriminated according to their geographical origin. Further differentiation has been achieved for samples produced industrially or in artisanal way.
Originality/value The present work explores the possibility of using mandatory oil quality chemical parameters, besides their original purpose, also to differentiate their geographical and production origin. The parameters were determined by simple and well-established analytical methods, applicable in every average laboratory for routine quality analysis
