Food adulteration is a growing concern worldwide. The collation and analysis of food adulteration cases is of immense significance for food safety regulation and research.
Research led by the Chinese Academy of Sciences collected 961 cases of food adulteration between 1998 and 2019 from the literature reports and announcements released by the Chinese government. Critical molecules were manually annotated in food adulteration substances as determined by food chemists, to build the first food adulteration database in China (http://www.rxnfinder.org/FADB-China/). This database is also the first molecular-level food adulteration database worldwide.
Additionally, the researchers propose an in silico method for predicting potentially illegal food additives on the basis of molecular fingerprints and similarity algorithms. Using this algorithm, we predict 1,919 chemicals that may be illegally added to food; these predictions can effectively assist in the discovery and prevention of emerging food adulteration.
The publication of this research has been published in Food Chemistry, doi: https://doi.org/10.1016/j.foodchem.2020.127010
The FADB-CHINA database has been added to the 'Services' page of the Food Fraud Mitigation section.