Group-type and fingerprint analysis of roasted food matrices (coffee and hazelnut samples) by comprehensive...

The present study is focused on the volatile fraction of roasted hazelnut and coffee samples, differing in botanical origins, morphological characteristics, and roasting treatments, selected as challenging matrices. Volatile components, sampled by headspace solid phase microextraction (HS-SPME), were analyzed by GC x GC-qMS, and separation results were adopted to classify, correlate, and/or compare samples and evaluate processing effects. The high-complexity sample profiles were interpreted through different methods: a group-type characterization, a direct fingerprint comparison, and a template matching to extract useful and consistent information, and advantages and limits of each specific approach were critically evaluated. The group-type analysis, focused on several known botanical and technological markers, enabled sample comparison and characterization based on their quali-quantitative distribution; it is highly reliable, because of the authentic standard confirmation, and extends the comparative procedure to trace and minor components. Fingerprint approaches (i.e., direct fingerprint comparison and template matching), on the other hand, extended sample comparisons and correlations to the whole volatiles offering an increased discrimination potential and improved sensitivity due to the wider analyte pattern considered. This study demonstrates the ability of comprehensive GC to further explore the complexity of roasted samples and emphasizes the advantages of, and the need for, a comprehensive and multidisciplinary approach to interpret the increased level of information provided by GC x GC separation in its full complexity.