A smartphone-detection strategy for accurate discrimination of Chinese teas via simultaneous sensing of infusion and aroma using multi-metal nanozymes.

The establishment of an efficient and accurate tea quality assessment system is of great significance for maintaining market order and protecting consumer rights. Compared with conventional large-scale instrumentation and manual sensory evaluation, the nanozyme-based sensor array approach offers the advantages of rapid analysis and cost-effectiveness. However, existing nanozyme sensor arrays primarily focus on analyzing tea infusions, where their inherent color often interferes with detection accuracy. To overcome this limitation, this study employs hydrogel-supported nanozymes capable of simultaneously sensing both tea infusion and tea aroma, thereby improving detection accuracy. Employing 2-aminothiophene-3-carboxamide with a compact structure as the ligand for nanozyme synthesis enables more efficient guidance of substrate reactions, enabling the simultaneous recognition of tea infusion and aroma. Furthermore, the interaction mechanisms between tea infusion, aroma, and the nanozymes were thoroughly investigated. Compared with methods relying solely on single-signal detection of tea infusion, this approach significantly improves detection accuracy to 98 %. To further optimize the sensor channels, a dimensionality reduction-based machine learning algorithm was introduced, which simplifies the signal processing workflow and enhances detection efficiency. Furthermore, the development of a mobile application provides a faster analytical basis for this novel synchronous functional detection device compared to traditional sensory evaluation.