A new technique using a chemical sensor (Gerstel, SPME ChemSensor System) consisting of a GC-MS (Agilent 6890-5973N) system with a Solid Phase MicroExtraction (SPME) autosampler (Gerstel, MPS 2) was applied to the analysis of flavor compounds in different beer sorts.
The flavor compounds were extracted by SPME and analyzed with the GC-MS. The obtained GC-MS data were used to identify the particular compounds and characterize the chemical composition of the beer fl avor. A chemometricspattern recognition software (Infometrix, Pirouette) was used for multivariate data analysis.
Freshly opened bottles from different beer sorts were used to build a model and represent the fresh grades. The variations in the fi ngerprint mass spectra of the different samples were analyzed using principal component analysis (PCA).
The composition spectrum of each sample becomes a dot on a 3-dimensional PCA plot. The dots from similar samples cluster together on the plot. Samples that differ in their flavor components due to different composition (different beer sorts or aging processes) group in different clusters.
If samples were classified to be different, the chemical sensor provided hints which ions were responsible. Extracted ion chromatograms were used to locate and identify the compounds that caused the sample to be different respectively aged.
