Volatile profile characterization of extra virgin olive oils from Argentina by HS-SPME/GC-MS and multivariate pattern recognition tools

Abstract

The distinctive aroma of virgin olive oil is attributed to a large number of chemical compounds of different classes such as aldehydes, alcohols, esters, hydrocarbons, ketones, furans, and other volatile compounds that are not yet identified. The aim of the present study lies in the characterization of compound volatile profile of the most representative olive oil cultivars produced in Argentina. The methodology proposed was based on the development of headspace (HS)-SPME/GC-MS with the subsequent analysis of the chemical fingerprints using a discriminant analysis method and a principal component analysis data compression strategy to distinguish olive oils from different varietal origins. Carboxen/polydimethylsiloxane (75 μm) fiber was the most efficient to trap volatile compounds. Optimization of the SPME conditions was also carried out using multivariate methods. To avoid the influence of factors other than the cultivar, olive trees were cultivated under the same agronomic and pedoclimatic conditions; olive fruits were picked at the same stage of ripeness, and their oils were extracted with the same processing system. Volatile fractions from oils of the analyzed cultivars consisted of a complex mixture of more than 40 compounds. Both quantitative and qualitative differences were found among cultivars. The analytical data association with multivariate analysis constitutes a reliable analytical tool with potential ability to discriminate monovarietal extra virgin olive oil from Argentina.