Multivariate analysis of NMR and FTIR data as a potential tool for the quality control of beer.

In this work, principal component analysis (PCA) is applied to the FTIR-ATR and the (1)H NMR spectra of 50 beers differing in label and type (ale, lager, alcohol-free), to identify the spectral parameters that may provide rapid information about factors affecting beer production. PCA of FTIR data resulted in the separation of beers mainly according to their alcoholic content, providing little information on components other than ethanol contributing to the variability within the samples. PCA of (1)H NMR spectra, performed on the region where major beer components resonate (3.0-6.0 ppm), resulted in the separation of samples into four groups: two groups characterized by the predominance of dextrins, one group of alcohol-free beers characterized by the predominance of maltose, and one group where glucose was found to predominate. By performing PCA on aliphatic and aromatic regions, the contribution of minor components was highlighted. In particular, most ales, lagers, and alcohol-free samples could be distinguished based on their aromatic composition, thus reflecting the high sensitivity of the low-field NMR region toward different types of beer fermentation.