LAUSR

Traceability offers significant information about the quality and safety of Chinese Angelica, a medicine and food homologous substance. In this study, a systematic four-step strategy, including sample collection, specific metal element fingerprinting, multivariate statistical analysis, and benefit-risk assessment, was developed for the first time to identify Chinese Angelica based on geographical origins. Fifteen metals in fifty-six Chinese Angelica samples originated from three provinces were analyzed. The multivariate statistical analysis model established, involving hierarchical cluster analysis (HCA), principal component analysis (PCA), and self-organizing map clustering analysis was able to identify the origins of samples. Furthermore, benefit-risk assessment models were created by combinational calculation of chemical daily intake (CDI), hazard index (HI), and cancer risk (CR) levels to evaluate the potential risks of Chinese Angelica using as traditional Chinese medicine (TCM) and food, respectively. Our systematic strategy was well convinced to accurately and effectively differentiate Chinese Angelica based on geographical origins.