Food metabolomics by GC×GC-TOF MS and Tandem Ionization: understanding the impact of climate events on edible crops quality

A better and comprehensive understanding of the relationship between climate conditions and nutrition is necessary to provide the human population with safe and secure access to food. The goal of the current study is to understand the effects of climate change on the detectable metabolome of hazelnuts regarding alternative post-harvest practices, as well as defects indirectly caused by global warming such as insect migrations that affect the quality of both peanuts and soy crops. The analytical strategy, aligned to food-metabolomics principles, exploits the information potential of multi-dimensional analysis that combine physicochemical discrimination/separation of analytes with spectrometric detection, such as comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) operating in Tandem Ionisation™. The process known as untargeted and targeted (UT) fingerprinting is used in combination with chemometric algorithms to highlight metabolomic variations between composite-class images generated by re-alignment and fusion of raw data collected from samples belonging to distinct classes, thus highlighting metabolites pattern differences. Data fusion, obtained by merging hard and soft ionization data streams, is capable to increase the information potential by exploiting both the standard MS fragmentation and higher overall sensitivity of the hard ionization and the wider dynamic range of response with an increased signal-to-noise ratio typical of the soft ionization. Moreover, aroma precursors involved in the Maillard reaction such as amino acids (i.e., threonine, valine, and tryptophan) and reducing sugars (i.e., glucose, fructose, saccharose) of both peanuts and hazelnuts were investigated to understand the quality discrepancy in the roasted products.