Quantitative Determination of Quality Parameters and Authentication of Vodka Using near Infrared Spectroscopy

Abstract

The objective of this study was to determine the potential of using near infrared (NIR) transmission spectroscopy to build calibration models for the quantitative characterisation and qualitative discrimination of Russian and non-Russian (foreign) vodkas. The results of partial least squares models based on the NIR spectra of 109 vodka samples showed that the major constituent alcoholic strength (root mean square error of prediction ( RMSEP) 0.25% vol) and the physical parameter relative density ( RMSEP 0.0003) could be successfully determined quantitatively. The method failed, however, in quantifying certain minor components such as anions, cations and sugars. For qualitative discrimination, soft independent modelling of class analogy analysis (SIMCA) and linear discriminant analysis (LDA) were applied to the sample set containing both the Russian and the foreign vodkas. Despite the correct assignment of unknown test samples to the respective vodka species, both modelling approaches, however, did not prove reliable enough for unambiguous authentication purposes.