Classification of wine distillates using multivariate statistical methods based on their direct GC-MS analysis

This work describes a novel methodology for the recognition of brandies based on direct injection of a raw sample followed by GC-MS analysis. Direct injection was chosen for its simplicity and the fact that the composition of the samples analysed remains unchanged compared to original brandy. The repeatability of the analytical procedure was evaluated by a comparison of the peak areas for randomly selected compounds obtained from 10 parallel measurements. A novel chemometric procedure was investigated in order to separate the samples studied on the basis of their geographical origin, processing technology or maturation time. In this procedure, a principal component analysis was applied to full chromatograms to select the time interval that shows the significant differences between the samples studied. It was shown that the chromatogram recorded at 36–39 min bore the maximal differences, hence it could be used to classify the brandy samples. The chromatographic peaks found within this time interval were identified and their peak areas determined. These compounds could be used as specific markers for determining geographical origin or processing technology.