Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe).

Food authenticity regarding different varieties and geographical origins is increasingly becoming a concern for consumers. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) and fast gas chromatography electronic nose (fast GC e-nose) were used to successfully distinguish the varieties and geographical origins of dried gingers from seven major production areas in China. By chemometric analysis, a distinct separation between the two varieties of ginger was achieved based on HS-GC-MS. Furthermore, flavor information extracted by fast GC e-nose realized the discrimination of geographical origins, and some potential flavor components were selected as important factors for origin certification. Moreover, several pattern recognition algorithms were compared in varietal and regional identification, and random forest (RF) led to the highest accuracies for discrimination. Overall, a rapid and precise method combining multivariate chemometrics and algorithms was developed to determine varieties and geographical origins of ginger, and it could also be applied to other agricultural products.