Taking 112 representative jasmine tea as research material, the quantitative calibration models for determining the contents of 13 chemical compositions such as total tea polyphenols (TP), free amino acids (AA), caffeine (CAFF), water extract, GA, GC, EGC, C, EC, EGCG, GCG, ECG, CG were established by NIRS combined with chemometrics. Q-value taking all important statistical values into account can evaluate the quality of models. Results showed that almost all the Q-value of models was 0.8~0.9, except for CG with a Q-value of 0.7702. Each of the 13 predictive models was applied for external inspection. Coefficients of correlation (R) between predicted value by NIR and the actual value were exceed 0.9, except CAFF and GCG was 0.7~0.8 and GC、EGCG、ECG、CG was 0.8~0.9. The established models present high stability and predictive accuracy. This paper provided a simple and convenient method for measuring the contents of major quality components in jasmine tea.
CHEN Mei-li
,
ZHANG Jun
,
GONG Shu-ying
,
TANG De-song
,
ZHANG Ying-bin
,
GU Zhi-lei
. Establishment of Predictive Model for Quantitative Analysis of Major Components in Jasmine Tea by Near Infrared Spectroscopy(NIRS)[J]. Journal of Tea Science, 2013
, 33(1)
: 21
-26
.
DOI: 10.13305/j.cnki.jts.2013.01.002
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