Discrimination of three Angelica herbs using LC-QTOF/MS combined with multivariate analysis

Abstract

Angelica gigas, a popular medicinal herb in Korea, is locally called Danggui; this name is similarly used for Angelica acutiloba and Angelica sinensis, which are also sold in the retail market. These three herbs have differing therapeutic effects and should be used according to their prescribed purposes. In some retail markets, though, all three herbs are known by the same common name rather than a scientific name and can therefore be confused with each other. In particular, in the case of powdered products, intentional or unintentional wrong sales activity by the seller may occur. In this study, non-targeted analysis was performed using liquid chromatography quadrupole time-of-flight mass spectrometry to discriminate between the three Angelica herbs, and marker compounds were identified by principal component analysis. Principal component analysis was applied to the whole dataset with the variables being sample name, peak name (m/z with retention time), and ion intensity extracted in advance by peak finding, alignment, and filtering. All three herbs were visually and clearly differentiated in the score plot, and the marker compounds that contributed to their discrimination were found in the loading plot through principal component variable grouping (PCVG). Among the marker compounds, coumarins contributed to the classification of A. gigas, and phthalides contributed to the classification of A. sinensis. The three Angelica herbs were well discriminated from each other. Within the three Angelica species investigated, marker compounds can determine the species of even powdered or extracted samples that cannot be visually identified.