The integration of MS-based metabolomics and multivariate data analysis allows for improved quality assessment of Zingiber officinale Roscoe

Abstract

Ginger (Zingiber officinale Roscoe) is consumed for health-promoting effects and as a food condiment. Comprehensive phytochemical analysis, other than gingerols and shogaols, has not yet been deeply investigated. Hence, the current research aimed to establish a non-targeted metabolomics approach for the discrimination between fresh ginger rhizome samples collected from four different producing countries, i.e., China, India, Pakistan, and Peru. In addition, lab-dried samples were analyzed to trace drying-induced metabolites. A comprehensive extraction procedure was carried out resulting in production of polar and non-polar fractions. The polar fraction was analyzed by ultra-performance liquid chromatography coupled with Fourier transform tandem mass spectrometry (UPLC-C18-FT-MS/MS) and gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF-MS) post derivatization. UPLC-C8-FT-MS/MS was used for analysis of non-polar fraction. Results revealed for identification of a total of 253 metabolites. In addition, multivariate data analysis (MVDA), including principal component analysis (PCA) demonstrated clustering of Asian specimens. Several metabolites with a characteristic pattern for the origin revealing the highest contents of bioactive metabolites in the Peruvian product. Moreover, chemical markers identified, including [6]-gingerol and [6]-shogaol discriminating between fresh and dried samples. Furthermore, abundances of some primary metabolites, including amino acids and cinnamic acid, have confirmed the biosynthetic pathway of gingerols and their transformation upon drying to shogaols. The proposed approach can be applied as a potential candidate for quality assessment of ginger and other medicinal plants.