绿茶茶汤中主要品质成分近红外定量分析模型的建立

doi:10.13305/j.cnki.jts.2011.04.002

Abstract

Abstract: Based on the large amounts of analyzing of major components in samples of green tea infusion, combining the chemical analysis results with near infrared spectra of tea infusion samples scanned by near infrared spectroscopy, this paper established and optimized quantitative analysis models of water extract, tea polyphenols, free amino acids, soluble sugars, caffeine, total catechins, EGCG, EC, EGC, EGC and GA by using partial least squares (PLS) method. Each of the 11 predictive models was applied for the external inspection. Results showed that almost all the decision coefficients of cross test and predictive models were exceed 95%, except for EGC and GA. RPDs of models were exceed 3, except for GA with a RPD of 2.67. The established models present high stability and predictive accuracy. This paper provided a new method for the analysis of major quality components in tea infusion and tea beverages by near infrared spectroscopy.

Key words: green tea, tea infusion, near infrared spectroscopy (NIRS), quantitative analysis, predictive model

CLC Number:

WANG Yu-xia, XU Rong-rong, REN Guang-xin, WANG Sheng-peng, WAN Xiao-chun, ZHANG Zheng-zhu. Establishment of the Predictive Models for Quantitative Analysis of Major Components in Green Tea Infusion by Near Infrared Spectroscopy (NIRS)[J]. Journal of Tea Science, 2011, 31(4): 355-361.

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Establishment of the Predictive Models for Quantitative Analysis of Major Components in Green Tea Infusion by Near Infrared Spectroscopy (NIRS)

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