Information fusion of hyperspectral imaging and self-developed electronic nose for evaluating the degree of black tea fermentation

Fermentation is a crucial step in the processing of black tea. Currently, the evaluation of the fermentation degree of black tea relies mainly on manual experience, which suffers from subjectivity and lacks quantifiability. This study proposed the fusion of hyperspectral imaging and electronic nose to evaluate the degree of black tea fermentation. The self-developed electronic nose was used to acquire aroma information, while hyperspectral imaging was used to obtain color and spectral information during the fermentation process. The samples were collected at different fermentation time including insufficient, moderate, and excessive fermentation. Then, the classification models were constructed based on individual types of information. Subsequently, the electronic nose data were fused with the hyperspectral data using different information fusion strategies (low-level, middle-level, high-level) and the classification models were built accordingly. Six types of classifiers were established. Results showed that with deeper levels of fusion, the accuracy of the model on the test set gradually improved. In the high-level fusion, the accuracy of the test set reached 100 %, with improvements of 10.34 % and 8.62 % compared with that solely based on electronic nose and hyperspectral imaging, respectively. This indicates that the proposed information fusion method is highly effective, providing state-of-the-art insights into and technologies for the evaluation of black tea fermentation degree.