为满足行业对茶叶品质成分检测设备的便携化、小型化以及快速化的迫切需求，自主研发出便携式近红外茶叶品质快速检测仪。文章系统介绍了该检测仪的整机结构与工作原理、主要部件设计和配套分析软件。收集全国13个不同产茶区不同等级的绿茶样品252个，采用偏最小二乘法（PLS）分别建立绿茶中的水分、茶多酚、氨基酸、咖啡碱和水浸出物含量的快速检测模型，并对模型预测效果进行验证。结果表明：游离氨基酸模型的定标标准偏差（SEC）和内部交互验证标准偏差（SECV）最小，分别是0.26、0.30，定标相关系数（RC）为0.92，模型预测值与真实值之间的线性回归系数为0.84。咖啡碱模型的SEC值和SECV值分别是0.36、0.38，RC为0.93，预测值与真实值之间的线性回归系数为0.87。茶多酚和咖啡碱模型外部验证的预测值与真实值之间的绝对偏差在0.50%以内。本研究结果为便携式近红外茶叶品质快速检测仪的推广提供技术支撑。

In order to meet the industry's urgent demand for portable, miniaturized and rapid detection equipment for tea quality components, a portable near-infrared tea quality detector was independently developed. This paper systematically introduced the structure, working principle, the main components and the supporting analysis software of the portable near-infrared tea detector. With the method of the partial least squares (PLS), 252 green tea samples of different grades collected from 13 different tea producing areas in China were used to establish the rapid detection models of water, tea polyphenols, amino acids, caffeine and water extracts in green tea, and the prediction effect of the models was verified. The results showed that the calibration standard deviation (SEC) and internal cross validation standard deviation (SECV) of free amino acid model were the smallest, which were 0.26 and 0.30 respectively, the calibration correlation coefficient (RC) was 0.92, andthe linear regression coefficient between the predicted value and the real value was 0.84. The SEC value and SECV value of caffeine model were 0.36 and 0.38 respectively, RC was 0.93, and the linear regression coefficient between the predicted value and the real value was 0.87. The absolute deviation between the predicted value and the real value of tea polyphenols and caffeine models was smaller than 0.50%. This study provides technical support for the popularization of portable near-infrared tea quality detector.

浙江省重点研发计划项目（2017C02007）