Establishment of Predictive Model for Quantitative Analysis of Tea Polyphenols and Caffeine of Souchong by Near Infrared Spectroscopy

LU Li; CHENG Xi; ZHANG Bo; SHEN Xiaoxia; LIU Yan; XIONG Li; YUAN Xiao; LI Yuanhua; LI Xinghui

doi:10.13305/j.cnki.jts.2020.05.014

2020 , Vol. 40 >Issue 5: 689 - 695

DOI: https://doi.org/10.13305/j.cnki.jts.2020.05.014

Research Paper

Establishment of Predictive Model for Quantitative Analysis of Tea Polyphenols and Caffeine of Souchong by Near Infrared Spectroscopy

LU Li ,
CHENG Xi ,
ZHANG Bo ,
SHEN Xiaoxia ,
LIU Yan ,
XIONG Li ,
YUAN Xiao ,
LI Yuanhua ,
LI Xinghui

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1. College of Tea and Food Sciences, Wuyi University, Wuyishan 354300, China;
2. College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China

Received date: 2020-06-12

Revised date: 2020-07-25

Online published: 2020-10-10

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Abstract

A total of 76 representative Souchong samples were studied. Quantitative models of tea polyphenols and caffeine of Souchong were established respectively by partial least squares (PLS). The chemical values of tea polyphenols and caffeine of 76 Souchong samples were measured by Chinese National Standard methods, combined with the near infrared spectrum. The results show that the R² and RMSEC values of tea polyphenols of calibration set were 97.59% and 0.566%. And the R² and RMSEP values of validation set were 95.06% and 0.855%. The R² and RMSEC values of caffeine of calibration set were 96.98% and 0.110%. And the R² and RMSEP values of validation set were 95.67% and 0.148%. The quantitative models had good prediction results, and could be used for rapid evaluation of the contents of tea polyphenols and caffeine in Souchong.

Key words： Souchong; near infrared spectroscopy (NIRS); tea polyphenols; caffeine; models

Cite this article

LU Li , CHENG Xi , ZHANG Bo , SHEN Xiaoxia , LIU Yan , XIONG Li , YUAN Xiao , LI Yuanhua , LI Xinghui . Establishment of Predictive Model for Quantitative Analysis of Tea Polyphenols and Caffeine of Souchong by Near Infrared Spectroscopy[J]. Journal of Tea Science, 2020 , 40(5) : 689 -695 . DOI: 10.13305/j.cnki.jts.2020.05.014

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