Metabolomics approach for the discrimination of raw and steamed Gastrodia elata using liquid chromatography quadrupole time-of-flight mass spectrometry.

A liquid chromatography quadrupole time-of-flight mass spectrometry-based metabolomics approach was applied to metabolite profiling of Gastrodia elata in order to identify raw and steamed G. elata and explore potential biomarkers for each processing state. A statistical classification method, significant analysis of microarrays, was used to select influential metabolites from the different forms. Through metabolite selection, several potential biomarkers were determined and assigned by matching mass information with that of reference compounds or by comparing it with data in the literature. Furthermore, the developed method was cross-checked using two validation procedures. The first validation was performed simultaneously with the metabolite profiling of G. elata using all detected metabolites, and the second was performed after the metabolite profiling using representative standard compounds of G. elata. Overall, this study can be applied to quality assurance of G. elata.