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The present study examines 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 two-dimensional gas chromatography (GC×GC) plane. The volatile fraction of Arabica green and roasted coffee samples differing in geographical origins and roasting treatments and the volatile fraction from juniper needles, sampled by headspace-solid phase microextraction, were analyzed by GC×GC-qMS and sample profiles processed by different approaches. In the target analysis profiling, samples submitted to different roasting cycles and/or differing in origin and post-harvest treatment are characterized on the basis of known constituents (botanical, technological, and/or aromatic 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 GC×GC to explore in depth the complexity of samples and emphasize the advantages of a comprehensive and multidisciplinary approach to improve the level of information provided by GC×GC separation.

Targeted and Non-Targeted Approaches for Complex Natural Sample Profiling by GC×GC-qMS