GC×GC combines an unmatched separation power with the capacity to generate highly ordered, structure- related patterns that help classification based on the analytes distribution in the 2D space. These features make GC×GC an excellent technique for the exhaustive characterization of complex samples such as those encountered in the food industry. The high level of detail obtained can be used for sample profiling, to identify signature markers responsible for flavor/taste, to evaluate different technological treatments, detect adulteration and guarantee authenticity. GC×GC-qMS is here used to compare and discriminate the volatile fractions of roasted hazelnuts from different varieties and geographical origin.
Volatile components were sampled by HS-SPME and analyzed by GC×GC-qMS. All chromatograms were obtained by using GC×GC based on an Agilent 6890 equipped with a Zoex KT 2004 loop type thermal modulator coupled with an Agilent 5975 MS detector. 2D data were displayed and analyzed using the Zoex GC Image software.
With the chromatographic fingerprinting approach 2D-peaks or 2D chromatographic regions are not identified and the attention is paid to the unique characteristics of the 2D plots. Thanks to the GC-Image software tools dedicated to advance fingerprinting (Image Investigator) a cumulative chromatogram of all samples is generated to identify all 2D regions with peaks to be used as distinctive features. These are compared to the individual samples chromatograms based on retention times and response intensity.
With the comprehensive template matching approach individual peaks (non-targeted or targeted) are individual features and the MS match factors are used to establish correct matching. Both methods use the features matching percentage to show (dis-)similarities between the samples.