Study on volatile markers of pasta quality using GC-MS and a peptide based gas sensor array

Headspace GC-MS (gas chromatography-mass spectrometry) and peptide based gas sensor array (E-nose) analysis were performed to evaluate the volatile fraction of durum wheat pasta samples of different commercial value and furosine content. A clear discrimination among high-price and low price samples of pasta was achieved using a simple PCA (Principal Component Analysis) of GC-MS dataset. This was attributed to the quality of semolina used in the process. Linear discriminant analysis (LDA) allowed discrimination among low or high furosine content in the samples. The peptide based a-nose was tested initially on a set of pure key volatiles found in GC-MS analysis and then on pasta samples. Discrimination of pasta samples having different commercial value was achieved. This work demonstrates that volatiles can be used to determine the quality of pasta with respect to semolina and thermal treatment. Moreover, the peptide-based e-nose represents a useful tool alternative to GC-MS to detect off-flavours and quality of the semolina in pasta.