This study attempted the feasibility to determine the ratio of tea polyphenols to amino acids in green tea infusion using near infrared (NIR) spectroscopy combined with synergy interval PLS (siPLS) algorithms. First, SNV was used to preprocess the original spectra of tea infusion; then, siPLS was used to select the efficient spectra regions from the preprocessed spectra. Experimental results showed that the spectra regions [7 8 18] were selected, which were out of the strong absorption of H2O. The optimal PLS model was developed with the selected regions when 6 PCs components were contained. The RMSEP value was equal to 0.316 and the correlation coefficient (R) was equal to 0.8727 in prediction set. The results demonstrated that NIR can be successfully used to determinate the ration of tea polyphenols to amino acids in green tea infusion.
This study discussed the feasibility of taste quality evaluation for green tea infusion using electronic tongue. Chemistry evaluation was regarded as the reference measurement, and used to measure total taste scores of green tea infusion. LS-SVM was used to build the correlativity between the sensor signals of green tea infusion and total taste scores by the reference measurement, and compared the influence of different principal components on the performance of LS-SVM model. Experimental results showed that the optimal model was obtained when 4 PCs were included with Rc=0.951 and RMSECV=3.242 in calibration set, Rp=0.904 and RMSEP=4.134 in the prediction set. This study showed that the electronic tongue had a great potential in the evaluation of taste quality for green tea and LS-SVM was an efficient method to build the evaluation model based on electronic tongue.
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