Zhang Shengsheng, Zuo Yamin, Wu Qing, Wang Jiao, Ban Lin, Yang Huili, Bai Zhiwen
Guizhou Key Laboratory for Information System of Mountainous Areas and Protection of Ecological Environment, Guizhou Normal University, 116 Baoshan North Rd, Guiyang, Guizhou 550001, China.
School of Basic Medical Sciences, Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, 30 Renmin South Rd, Shiyan, Hubei 442000, China.
J Anal Methods Chem. 2021 Nov 15;2021:9563162. doi: 10.1155/2021/9563162. eCollection 2021.
The quality of tea leaves (e.g., their color, appearance, and taste) can be directly influenced by the tea production process, which is closely connected with the content of a number of chemical components formed during the production of the tea leaves. However, the production process is now controlled by people's experience, making its quality significantly different. NIRS is a time-saving, cost-saving, and nondestructive method. Therefore, it is necessary to introduce NIRS technology into the quality control of the tea production process. In this study, a quantitative analysis model of caffeine, epigallocatechin-3-gallate (EGCG), and moisture content was established by near-infrared spectroscopy (NIRS) which was united simultaneously with partial least squares (PLSR) for online process monitoring of tea production. The model parameters show that the established model has fine robustness and outstanding measuring accuracy. Then, the feasibility of the established method is verified by the traditional method. Through the verification of the precision of the instrument and the stability of the sample, it is clarified that the model can be further utilized to monitor tea product quality online in a productive process.
茶叶的品质（如色泽、外观和口感）会受到茶叶生产过程的直接影响，而这一过程与茶叶生产过程中形成的多种化学成分的含量密切相关。然而，目前生产过程由人们的经验控制，导致其质量差异显著。近红外光谱法（NIRS）是一种省时、省钱且无损的方法。因此，有必要将NIRS技术引入茶叶生产过程的质量控制中。在本研究中，通过近红外光谱（NIRS）并结合偏最小二乘法（PLSR）建立了咖啡因、表没食子儿茶素-3-没食子酸酯（EGCG）和水分含量的定量分析模型，用于茶叶生产的在线过程监测。模型参数表明所建立的模型具有良好的稳健性和出色的测量精度。然后，用传统方法验证了所建立方法的可行性。通过对仪器精度和样品稳定性的验证，明确了该模型可进一步用于生产过程中茶叶产品质量的在线监测。
