Thin-layer chromatography-surface-enhanced Raman spectroscopy and chemometric tools applied to Pilsner beer fingerprint analysis

This work proposes a novel use of thin-layer chromatography with detection by surface enhancement Raman spectroscopy (SERS) to generate chromatographic and spectral fingerprints of complex samples, aiming toward samples classification. Ten commercial beer brands were analyzed in order to verify clusters related to each brand and the brewery location. The samples were eluted in thin-layer chromatography plates and sprayed by gold nanoparticles colloidal solution using a simple and cheap lab-made apparatus. The plates were analyzed by SERS, so, at the end of the measurement, one SERS-chromatogram matrix was acquired for each sample. The high sensitivity of the SERS analysis allows the detection of compounds in low concentrations, unseen via common thin-layer chromatography detection procedures, increasing the information for fingerprint analyses. Because of the high complexity of the sample, coelution problems and slight shifts in chromatographic peaks might appear in this kind of analysis; it was necessary to use chemometric tools for data analysis. Two chemometric methods of data deconvolution were compared, multivariate curve resolution-alternating least squares and independent component analysis. From the chromatographic peaks recovered by both methods, it was possible to perform a fingerprint analysis using principal component analysis, which allowed identifying patterns among the samples according to the brands and brewery location of Pilsner beers produced in Brazil. Copyright (c) 2017 John Wiley & Sons, Ltd.