The volatile compositions of 192 olive oil samples from five different European countries were investigated by PTR-MS sample headspace analysis. The mass spectra of all samples showed many masses with high abundances, indicating the complex VOC composition of olive oil. Three different PLS-DA models were fitted to the data to classify samples into ‘country’, ‘region’ and ‘district’ of origin, respectively. Correct classification rates were assessed by cross-validation. The first fitted model produced an 86% success rate in classifying the samples into their country of origin. The second model, which was fitted to the Italian oils only, also demonstrated satisfactory results, with 74% of samples successfully classified into region of origin. The third model, classifying the Italian samples into district of origin, yielded a success rate of only 52%. This lower success rate might be due to either the small class set, or to genuine similarities between olive oil VOC compositions on this tight scale.

In the present study, proton transfer reaction-mass spectrometry (PTR-MS) in combination with partial least square-discriminant analysis (PLS-DA) was evaluated as a method for the prediction of the origin of European butters. Eighty-three commercial butters from three European regions were subjected to headspace analysis using PTR-MS. Data were collected for the mass range m/z 20–150 using a dwell time of 0.2 s mass−1, resulting in a cycle time just under 30 s. The log transformed headspace concentrations of the masses were subjected to PLS-DA in order to estimate classification models for the butter samples. One model predicted the region of origin; a second set of models predicted dichotomously whether or not a butter originated from a particular EU country. The performance of each model was evaluated by means of a 10-fold double cross validation procedure. For 76% of the butters the region of origin was predicted correctly in the cross validation. The success rate of the countries, averaged over all dichotomous models, was 88% but large differences between countries were observed. Additional work is required to study the underlying factors that determine the geographical differences in butter volatile compositions.