<p>Potential risks in tea arise from the entire process, from field to table. A comprehensive summary of harmful substances is very important for understanding the risks associated with tea products. These potential hazards should be monitored using various detection methods. This review aims to emphasize potential risks in tea, including endogenous risks (acrylamide, polycyclic aromatic hydrocarbon, and others) in tea processing and exogenous hazardous substances (heavy metals, pesticides, microorganism and toxins, microplastics and nanoplastics, bisphenol A, and pyrrolizidine alkaloids). Meanwhile, emerging monitoring technologies are summarized for ensuing the quality and safety of tea product, such as electronic nose, spectral techniques, chromatography, electrochemistry, nano-biosensors, and artificial intelligence. Challenges and perspectives are proposed to improve the quantitative analysis. In the future, the efficient cooperation between tea plantations, manufacturers, logistics and sellers can be achieved by blockchain, machine learning and big data. This review provides a foundation for evaluating risks of tea, thereby ensuring food safety and protecting consumer health.</p>

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Potential risks in tea and emerging monitoring technologies: a review

  • Tao Yang,
  • Xingyu Lin,
  • Yanqun Xu,
  • Zhonghua Liu,
  • Zisheng Luo

摘要

Potential risks in tea arise from the entire process, from field to table. A comprehensive summary of harmful substances is very important for understanding the risks associated with tea products. These potential hazards should be monitored using various detection methods. This review aims to emphasize potential risks in tea, including endogenous risks (acrylamide, polycyclic aromatic hydrocarbon, and others) in tea processing and exogenous hazardous substances (heavy metals, pesticides, microorganism and toxins, microplastics and nanoplastics, bisphenol A, and pyrrolizidine alkaloids). Meanwhile, emerging monitoring technologies are summarized for ensuing the quality and safety of tea product, such as electronic nose, spectral techniques, chromatography, electrochemistry, nano-biosensors, and artificial intelligence. Challenges and perspectives are proposed to improve the quantitative analysis. In the future, the efficient cooperation between tea plantations, manufacturers, logistics and sellers can be achieved by blockchain, machine learning and big data. This review provides a foundation for evaluating risks of tea, thereby ensuring food safety and protecting consumer health.