Rapidly analyzing of ingredients during chewing and processing of areca nut using feature-based molecular networking

Abstract

As a traditional herbal medicine and food in China and many other Asian countries, the areca nut (Areca catechu L.) is not only widely used for the treatment of various diseases, but also popular as a chewing hobby. However, as a first-class carcinogen designated by IARC, clinical studies have shown that long-term chewing of areca nut is associated with oral mucosal diseases and even oral cancer. Moreover, the incidence of these diseases varies regionally, suggesting that it may be related to edible methods in different regions. In this study, UPLC-Q-TOF-MSE was combined with feature-based molecular networking to systematically characterise the chemical ingredients of areca nut. Based on these results, the ingredients of different edible parts and edible methods was rapidly compared. The compositional changes during the production process were also analysed. The obtained results provide a foundation for the scientific utilisation of areca nut.

Keywords: Areca nut; Edible methods; Edible parts; Feature-based molecular networking; Ingredients comparison; UPLC-Q-TOF-MSE.