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茶叶科学 ›› 2011, Vol. 31 ›› Issue (4): 355-361.doi: 10.13305/j.cnki.jts.2011.04.002

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绿茶茶汤中主要品质成分近红外定量分析模型的建立

王玉霞, 徐荣荣, 任广鑫, 王胜鹏, 宛晓春, 张正竹*   

  1. 农业部茶及药用植物安全生产重点开放实验室,安徽农业大学,安徽 合肥 230036
  • 收稿日期:2011-01-25 修回日期:2011-03-25 出版日期:2011-08-15 发布日期:2019-09-09
  • 通讯作者: zzz@ahau.edu.cn
  • 作者简介:王玉霞(1985— ),女,山东菏泽人,硕士研究生,主要从事茶叶生物化学与天然产物方面的研究。
  • 基金资助:
    农业部948项目“茶叶水分在线检测和品质分析技术引进”(2011-Z28)和农业科技成果转化资金项目“茶鲜叶原料质量近红外分析仪的中试”(2010GB2C300204)共同资助

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

WANG Yu-xia, XU Rong-rong, REN Guang-xin, WANG Sheng-peng, WAN Xiao-chun, ZHANG Zheng-zhu*   

  1. Key Laboratory of Tea & Medicinal Plants and Product Safety, Ministry of Agriculture, Anhui Agricultural University, Hefei 230036 China
  • Received:2011-01-25 Revised:2011-03-25 Online:2011-08-15 Published:2019-09-09

摘要: 以绿茶茶汤为分析对象,在分析大量绿茶茶汤中主要品质成分含量的基础上,利用近红外光谱技术将化学分析结果与扫描茶汤样品得到的近红外光谱对应起来,采用偏最小二乘法(PLS)进行优化分析,建立了绿茶茶汤中水浸出物、茶多酚、游离氨基酸、可溶性糖、咖啡碱、儿茶素总量、表没食子儿茶素没食子酸酯(EGCG)、表儿茶素(EC)、表没食子儿茶素(EGC)、表儿茶素没食子酸酯(ECG)、没食子酸(GA)共11个指标或组分的定量分析模型,并对这11个模型分别进行了外部检验。结果表明,除ECG和GA外,其余指标或组分分析模型的交叉检验和预测模型的决定系数都在95%以上;除GA预测集RPD为2.67外,其余模型的RPD都在3以上,模型的稳定性和预测准确性较高。研究结果为利用近红外光谱技术分析茶汤或茶饮料中主要品质成分提供了新方法。

关键词: 绿茶, 茶汤, 近红外光谱, 定量分析, 预测模型

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

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