A novel approach to assess the quality and authenticity of Scotch Whisky based on gas chromatography coupled to high resolution mass spectrometry

Highlights: • Two sample handling strategies were compared for isolation of whisky components. • Non-target fingerprinting of Scotch Whiskies by GC-Q-TOF was applied. • Chemometric methods were employed for the assessment of the authenticity. • Characteristic markers were found and tentatively identified. • Identification of fake samples based on GC-Q-TOF fingerprints is documented. - Abstract: Whisky is one of the most popular spirit drinks in the world. Unfortunately, this highly valued commodity is vulnerable to fraud. To detect fraudulent practices and document quality parameters, a number of laboratory tests based on various principles including chromatography and spectroscopy have been developed. In most cases, the analytical methods are based on targeted screening strategies. Non-targeted screening (metabolomics fingerprinting) of (semi)volatile substances was used in our study. Following the pre-concentration of these compounds, either by solid phase microextraction (SPME) or by ethyl acetate extraction, gas chromatography (GC) coupled to tandem mass spectrometry (Q-TOF mass analyser) was employed. Unsupervised principal component analysis (PCA) and supervised partial least squares discriminant analysis (PLS–DA) were used for evaluation of data obtained by analysis of a unique set of 171 authentic whisky samples provided by the Scotch Whisky Research Institute. Very good separation of malt whiskies according to the type of cask in which they were matured (bourbon versus bourbon and wine) was achieved, and significant ´markers' for bourbon and wine cask maturation, such as N-(3-methylbutyl) acetamide and 5-oxooxolane-2-carboxylic acid, were identified. Subsequently, the unique sample set was used to construct a statistical model for distinguishing malt and blended whiskies. In the final phase, 20 fake samples were analysed and the data processed in the same way. Some differences could be observed in the (semi)volatile profiles of authentic and fake samples. Employing the statistical model developed by PLS-DA for this purpose, marker compounds that positively distinguish fake samples were identified.