Advances in research on novel technologies for the detection of exogenous contaminants in traditional Chinese medicine
Ziyu Guo, Junyao Li, Lan Zeng, Ping Wang, Meifang Li, Chang Su, Shuhong Wang
Abstract
Exogenous contaminants in traditional Chinese medicine (TCM), including pesticide residues, heavy metals, mycotoxins, and sulfur dioxide residues, pose significant risks to human health and environmental safety. Conventional detection methods are limited by insufficient sensitivity, complex sample preparation, and challenges in multi-residue analysis, compromising accuracy and efficiency. To address these critical bottlenecks-particularly the escalating regulatory demands and trade barriers due to contamination incidents-this review establishes the first integrated 'dual track' quality control framework for TCM contaminants. We propose a novel risk stratified strategy synergizing laboratory grade accuracy with field deployable screening, overcoming the sensitivity portability trade-off. This work provides a roadmap for establishing globally harmonized standards. Future research should prioritize high-throughput methods, intelligent analytics, and green detection technologies. Integrating AI-driven automation with data traceability could establish unified systems for contaminant detection and degradation, enhancing TCM quality control and global competitiveness.