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Identification of fake green tea is performed by sensory assessment which has significant drawbacks in terms of objectivity. In this works, sensory assessment and electronic tongue were utilized for identifying fake green tea. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were used to assess the feasibility and effectiveness of discrimination of electronic tongue. The PCA and HCA revealed a distinct separation between samples, which corresponded with the results of sensory assessment. Artificial Neural Network (ANN), including back propagation neural network with the Levenberg-Marquardt training algorithm (LMBP) and radial basis function neural network (RBF), were used as an automatic classifier and showed good performance in the training set and the prediction set. The results suggest that electronic tongue can be used for distinguishing fake Dongting Biluochun Tea from certified products characterized by protection of geographical indications product certification with pattern recognition methods instead of sensory assessment.

Identification of Fake Green Tea by Sensory Assessment and Electronic Tongue