Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

Abstract

This study provides the first assessment of the volatile metabolome map of Tuber Aestivum and Tuber Borchii originating from Greece using headspace solid-phase micro-extraction (HS-SPME) coupled to gas chromatography-mass spectrometry (GC-MS). For the extraction of the volatile fraction, the SPME protocol was optimized after examining the effects of sample mass, extraction temperature, and extraction time using the one-variable at-a-time approach (OVAT). The optimum parameters involved the extraction of 100 mg of homogenized truffle for 45 min at 50°C. Overall, 19 truffle samples were analyzed, and the acquired data were normalized and further processed with chemometrics. Agglomerative hierarchical clustering (HCA) was used to identify the groups of the two species. Partial least squares-discriminant analysis (PLS-DA) was employed to develop a chemometric model that could discriminate the truffles according to the species and reveal characteristic volatile markers for Tuber Aestivum and Tuber Borchii grown in Greece.