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基于光谱技术的茶叶品质参数茶多酚含量快速检测方法研究

A Study on Rapid Detection Method of Tea Polyphenol Content Based on NIRS Technology in Tea Quality Parameters

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摘要

茶多酚是茶叶中的主要成分, 其含量约占30%左右, 决定着茶汤的味道、颜色等。利用近红外光谱法对茶多酚含量进行快速检测, 在茶叶品质的快速识别中具有极高的实用价值。基于光谱技术结合化学计量学方法, 对不同茶叶的不同成分进行了研究, 结果表明: 茶叶中的主要成分茶多酚含量与近红外波段(1800~2500nm)的吸光度存在近似的线性关系, 在此基础上建立拟合曲线, 得出了不同拟合曲线的相关系数和校正均方根误差; 采用近红外光法结合偏最小二乘法在1872nm建立了茶多酚含量预测模型, 其相关系数达到0.9378, 均方根误差为0.008015。

Abstract

Tea polyphenol is the main component in tea. The content of tea polyphenols accounts for about 30%, which determines the taste and color of tea soup. Therefore, how to use the NIRS to quickly detect the content of tea polyphenols has a very high practical value in the rapid identification of tea quality. On the basis of the combination between NIRS and chemometrics methods, this paper analyzes the components of different teas. The tests indicate that, there is an approximately linear relationship between tea polyphenol content and the absorbance in the near-infrared waveband (1800~2500nm). Based on this result, a fitting curve was established, and the correlation coefficient and the correction root mean square error of different fitting curves were obtained. The tea polyphenol content prediction model was established using near-infrared light method and partial least squares method at 1872nm. The correlation coefficient reached 0.9378, the RMSE is 0.008015.

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中图分类号:O433.4

DOI:10.16818/j.issn1001-5868.2018.04.029

所属栏目:光电系统

基金项目:国家自然科学基金项目(51276209).

收稿日期:2018-03-04

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作者单位    点击查看

赵雅:重庆第二师范学院, 重庆 400065
王博思:重庆车辆检测研究院, 重庆 401122
赵明富:重庆理工大学, 重庆 400054

联系人作者:赵雅(yazhao122@foxmail.com)

备注:赵雅(1990-), 女, 重庆人, 助教, 硕士, 主要从事旅游管理、茶叶品质鉴定等方面的研究。E-mail: yazhao122@foxmail.com

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引用该论文

ZHAO Ya,WANG Bosi,ZHAO Mingfu. A Study on Rapid Detection Method of Tea Polyphenol Content Based on NIRS Technology in Tea Quality Parameters[J]. Semiconductor Optoelectronics, 2018, 39(4): 591-594

赵雅,王博思,赵明富. 基于光谱技术的茶叶品质参数茶多酚含量快速检测方法研究[J]. 半导体光电, 2018, 39(4): 591-594

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