Targeted and non-targeted approaches for complex natural sample profiling by GCxGC-qMS

The present study examined the ability of targeted and non-targeted methods to provide specific and complementary information on groups of samples on the basis of their component distribution on the GCxGC chromatographic plane. The volatile fraction of Arabica green and roasted coffee samples, differing for geographical origins and roasting treatments, and the volatile fraction from juniper needles, sampled by Headspace-Solid Phase Micro Extraction (HS-SPME), were analyzed by GCxGC-q-MS and sample profiles processed by different approaches. In the target analysis profiling, samples, submitted to different roasting cycles and/or differing in their origin and postharvest treatment, are characterized on the basis of known constituents (botanical, technological and/or aroma markers). This approach provides highly reliable results on quali-quantitative compositional differences, because of the authentic standard confirmation, extending and improving the specificity of the comparative procedure to trace and minor components. On the other hand, non-targeted data-processing methods, e.g., direct image comparison and template-based fingerprinting, include in the sample comparisons and correlations all detected sample components offering an increased discrimination potential by identifying compounds that are comparatively significant but not known targets. Results demonstrate the ability of GCxGC to explore in depth the complexity of samples and emphasizes the advantages of a comprehensive and multidisciplinary approach to improve the level of information provided by GCxGC separation.