The utilization of a data fusion approach to investigate fingerprint profiles of dark tea from China's different altitudes.

Dark tea refers to a kind of post-fermented product, and its quality and price vary owing to the distinct altitudes at which it grows. In this study, a novel method based on high performance liquid chromatography with a diode-array detector (HPLC-DAD) and an evaporative light scattering detector (HPLC-ELSD) was proposed for the classification of dark teas from distinct altitudes in China. Through implementing a strategy fusing feature-level data to construct a combined dataset, the classification performance of dark teas from distinct altitudes in China was evaluated after preprocessing. The results suggested that, through the feature fusion strategy, the identification accuracy rate increased from <70% of a single detector to 76.923%. After the implementation of preprocessing, the identification accuracy rate was further improved. Typically, the model identification accuracy rate after short-time Fourier Transform (STFT) treatment reached 92.85%, and the AUROC value was higher than 0.84, exhibiting a favorable generalization ability. This study provides a new thinking for the identification technology of dark teas from different altitudes in China.