Chemical Blueprint of food: is GCxGC mature in this respect

The concept of “blueprint” in the food chemistry field has been exploited by the Molecular Sensory Science defining the so-called key-aroma compounds that unequivocally evoke, if properly distributed in terms of quali-quantitative profile, the characteristic food aroma (Christlbauer 2009). This concept can be extended to a wider group of sample attributes and fruitfully adopted for classification and comparative processes. In this perspective, for example, it is possible to recognize a sample “technological” blueprint that includes chemicals, strongly related to industrial or artisanal treatments a raw matrix undergoes to be transformed in a food-end product, or a “safety” blueprint that refers to the presence (above a certain threshold) of specific contaminants to be monitored. Multidimensional separation techniques, and in particular, comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GCxGC-MS), has demonstrated to be a powerful tool to deeply investigate complex mixtures of food interest due to the enhanced peak capacity compared to one-dimensional GC (Adahchour 2008, Pierce 2008, Cordero 2010a). In particular, non-targeted fingerprint analysis has demonstrated to be successfully in revealing qualitative/quantitative differences in chemical compositions facilitating the identification of potential marker compounds (Almstetter 2009), and grouping and classification of samples (Cordero 2008, Cordero 2010b). Current research is mainly focused in the development of non-targeted, peak-based fingerprinting methods able to exploit the informative content of three dimensional GCxGC-MS data sets to maximize the information extractable from each single analysis (Reichenbach 2012). Moreover, GCxGC can be considered a mature technique, thanks also to the technological advancements recently introduced that have simplified the instrumental set-up making it easier to adopt multidimensional GC as a routine control technique. In this perspective the chemical “blueprint”, embodied in the GCxGC sample fingerprint, should be easily revealed and subsequently adopted ad a discriminating tool. In particular, becomes of crucial importance the development of suitable informative tools able to act as Analytical Decision Makers (Sandra 2004) enabling the analyst to decide whether or not a sample necessitates of a further detailed analysis to clarify its composition. Complex food samples of vegetable origin have been analyzed by GCxGC-MS and GCxGC-FID and sample “blueprints” revealed and adopted, as analytical probe, to categorize samples on the basis of their aroma quality, process impact and safety compliance