The identification of key components relevant to sensory perception of quality from commercial chocolate samples was accomplished after chemometric processing of GC×GC-MS (Comprehensive Two-dimensional Gas Chromatography with Mass Spectrometric Detection) profiles corresponding to HS-SPME (Headspace Solid Phase Microextraction) extracts of the samples. Descriptive sensory evaluation of samples was carried out using Optimized Descriptive Profile (ODP) procedures, where sensory attributes of 24 commercial chocolate samples were used to classify them in two classes (low and high chocolate flavor). 2D Fisher Ratio analysis was applied to four-way chromatographic data tensors (1st dimension retention time 1tR × 2nd dimension retention time 2tR × m/z × sample), to identify the crucial areas on the chromatograms that resulted on ODP class separation on Principal Component Analysis (PCA) scores plot. Comparing the relevant sections of the chromatograms to the analysis of the corresponding mass spectra, it was possible to assess that most of the information regarding the sample main sensory attributes can be related to only 14 compounds (2,5-dimethylpyrazine, 2,6-dimethyl-4-heptanol, 1-octen-3-ol, trimethylpyrazine, β-pinene, o-cimene, 2-ethyl-3,5-dimethylpyrazine, tetramethylpyrazine, benzaldehyde, 1,3,5-trimethylbenzene, 6-methyl-5-hepten-2-one, limonene, benzeneethanol and 1,1-dimethylbutylbenzene) among the complex blend of volatiles found on these extremely complex samples.
Corrigendum to “Effective feature selection based on Fisher Ratio for snoring recognition using different validation methods” [Appl. Acoust. 185 (2022) 108429:1–8]
