Quality Study Of Tea Color, Aroma And TasteBased On Sensory Evaluation And Chemometrics

There are many kinds of tea in China and their quality characteristics are different. Determination of chemical components is usually used for tea quality evaluation and the results are relatively accurate and objective. But the operations are complex, and results cannot reflect the overall quality of tea. Sensory evaluation can identify tea quality by human senses. Though easily affected, it can evaluate tea quality acutely and fast, and express its advantages well companied with instruments. Feasibility of the use of modern science and instrument analysis technology to realize intelligent sense in tea quality evaluation was discussed from tea infusion, aroma and taste in this study.Color parameter of green tea, black tea and jasmine tea were determined by color photometer. And the regression equations between score of tea infusion color and L*,a*,b*value were established, which could take on more than80%of original message. The external validation showed that prediction accuracy of tea infusion score of green tea, black tea and jasmine tea were75%,81.25%and52.17%respectively when difference within±3points(not including3points) between real value and predicted value was considered to be proper. Additionally, parameter of color series of green tea and tea infusion characteristic description of sensory evaluation had certain relevances.Response value of the electronic nose(EN) sensors and characteristics of green tea aroma were studied by stepwise discriminant analysis(SDA). SDA results of9regions showed that recognition accuracy of back substitution and cross-validation were84.4%and79.2%respectively for the9discriminant functions. But the feasibility of discrimination to different kinds of aroma using EN data was not enough, and the effects of classification were poor.Based on analysis of conventional chemical components to8kinds of green tea taste, we found that content of water extract made great contributions to tea infusion concentrations. And ester catechins especially EGCG had great effects on astringency. Furthermore, high performance liquid chromatography(HPLC) data was studied by matlab software through cluster analysis and heatmaps that could contribute to identifying characteristic components were acquired. Results showed that GA, EGC, caffeine and GCG made little contributions to difference in tea taste, while C, GC, EC, ECG, EGCG and CG made great contributions to it among these known components, and mainly including No.3,12,15,17,20,23,29,41,43,47,49～53components in HPLC data. Their contents or composition differences formed their own different taste characteristics.