This study aims to determine volatile compounds in red wines of Zweigelt and Rondo varieties using HS-SPME/GC-MS (headspace solid-phase microextraction gas chromatography - mass spectrometry), and to find a marker and/or a classification model for the assessment of varietal authenticity. Wines were produced from the two varieties, and 67 volatile compounds were tentatively identified in the test wines. The relative concentrations of volatiles were used as an input data set, divided into two subsets (training and testing), to the support vector machine (SVM) and k-nearest neighbor (kNN) algorithms. A subset of 6 volatiles was chosen for evaluation, and it was found that 2 of the volatiles in particular gave an accuracy of 100%. One of the chosen volatiles in Zweigelt wines was absent from the Rondo wines. Further chemometric analysis identified two further volatiles of importance for SVM . The classification model approach needs expanding for mixed varieties, and when the same varietal wines are produced in different geographical locations.
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