茶叶品质在线检测仪设计与试验  

Design and Experiment of the Tea Quality Online Detector

作　　者：王家鹏[1,2] 周新奇 冯海强 肖志鹏 范起业 WANG Jiapeng;ZHOU Xinqi;FENG Haiqiang;XIAO Zhipeng;FAN Qiye(Hangzhou Tea Research Institute,CHINA COOP,Hangzhou 310016,China;Zhejiang Key Laboratory of Transboundary Applied Technology for Tea Resource,Hangzhou 310016,China;Hangzhou Puyu Technology Development Co.,Ltd.,Hangzhou 311305,China;Zhejiang Provincial Agricultural Technology Extension Center,Hangzhou 310020,China)

机构地区：[1]中华全国供销合作总社杭州茶叶研究所,浙江杭州310016 [2]浙江省茶资源跨界应用技术重点实验室,浙江杭州310016 [3]杭州谱育科技发展有限公司,浙江杭州311305 [4]浙江省农业技术推广中心,浙江杭州310020

出　　处：《中国茶叶加工》2024年第4期18-25,共8页China Tea Processing

基　　金：浙江省农业重大技术协调推广计划项目(2022XTTGCY04-05);浙江省科技计划项目(2022C02075)。

摘　　要：为满足茶叶加工过程中对茶叶品质成分在线检测的迫切需求,基于近红外光谱技术,设计了茶叶品质在线检测仪。文章系统介绍了检测仪的整机结构、工作原理、主要部件和配套分析软件。采集不同杀青程度的杀青叶样品280个,采用偏最小二乘法(PLS)建立杀青叶咖啡碱、水浸出物、茶多酚、含水率和游离氨基酸含量的检测模型,并对模型进行内部交叉验证和外部验证。结果表明,含水率模型的校准标准误差(SEC)和交叉验证标准误差(SECV)分别是0.44、0.47,两者偏差最小,为0.03,校正相关系数(RC)为0.92;咖啡碱模型的SEC和SECV分别是0.43、0.35,RC为0.95;且两者的预测值与真实值间的线性回归系数均在0.90以上。含水率和咖啡碱模型外部验证的预测值与真实值之间的平均绝对偏差在1.00%以内,分别是0.68%、0.80%。设计的茶叶品质在线检测仪的稳定性和精度满足现场实时检测需求,为茶叶加工设备智能化提供了技术支撑。To meet the urgent need for online detection of tea quality components during tea processing,a tea quality online detection instrument was developed based on near-infrared spectroscopy technology.This paper systematically introduces the overall structure,working principle,key components,and accompanying analysis software of the detection instrument.280 samples of fixed leaves with different degrees of fixation were collected,and a detection model was established for caffeine,water extract,tea polyphenols,moisture content,and free amino acid content in fixed leaves using partial least squares(PLS).Internal and external cross validation of the model were conducted.The results showed that the standard error of calibration(SEC)and standard error of cross validation(SECV)for the moisture content model were 0.44 and 0.47,respectively,with a minimal difference of 0.03,and the calibration coefficient(Rc)reached 0.92;For the caffeine model,the SEC and SECV were 0.43 and 0.35,respectively,and the Rc reached 0.95;The linear regression coefficients between predicted values and actual values for both models exceeded 0.90.The external validation of the moisture content and caffeine models showed that the mean absolute deviation between predicted and actual values was within 1.00%,specifically 0.68%and 0.80%,respectively.In summary,the developed tea quality online detection instrument exhibits good stability and precision,meeting the needs of real-time field detection and providing technical support for the intelligentization of tea processing equipment.

关 键 词：近红外 在线检测 茶叶 品质成分 模型 

分 类 号：TS272.5[农业科学—茶叶生产加工]