Comprehensive characterization of flavor compounds in berry by HS-SPME-GCMS combined with AntDAS-GCMS for geographical discrimination.

The accurate and comprehensive characterization of flavor compounds in Ningxia berry (Lycii Fructus) to provide an accurate geographical discrimination model remains unrealized. Here, a novel strategy that integrates headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) with our newly developed GC-MS data analysis software, AntDAS-GCMS, was employed for the accurate tracing of samples from typical cultivated zones of China, including Ningxia, Gansu, Qinghai, and Xinjiang province. Parameters of HS-SPME were optimized using the resolved components from AntDAS-GCMS. Information on volatile compounds (VOCs) was collected with GC-MS under the optimized HS-SPME. Raw GC-MS data files were automatically analyzed via AntDAS-GCMS to perform component resolution, time-shift correction and registration, chemometric analysis, and compound identification. A total of 275 components were screened, based on which 30 VOCs were identified. Four chemometric models were evaluated through Monte-Carlo simulation, and the partial least squares-discrimination provided the best geographical discrimination performance with the identified compounds.