多酚
多酚氧化酶
绿茶
食品科学
判别式
化学
风味
支持向量机
生物系统
传感器阵列
基质(水族馆)
鉴定(生物学)
模式识别(心理学)
数学
植物
人工智能
生物
计算机科学
酶
生物化学
抗氧化剂
统计
过氧化物酶
生态学
作者
Xiaoyu Yang,Bin Zou,Xinjian Zhang,Jie Yang,Zhichun Bi,Hui Huang,Yongxin Li
标识
DOI:10.1016/j.bios.2024.116056
摘要
Green tea is popular among consumers because of its high nutritional value and unique flavor. There is often a strong correlation among the type of tea, its quality level and the price. Therefore, the rapid identification of tea types and the judgment of tea quality grades are particularly important. In this work, a novel sensor array based on nanozyme with polyphenol oxidase (PPO) activity is proposed for the identification of tea polyphenols (TPs) and Chinese green tea. The absorption spectra changes of the nanozyme and its substrate in the presence of different TPs were first investigated. The feature spectra were scientifically selected using genetic algorithm (GA), and then a sensor array with 15 sensing units (5 wavelengths × 3 time) was constructed. Combined with the support vector machine (SVM) discriminative model, the discriminative rate of this sensor array was 100% for different concentrations of typical TPs in Chinese green tea with a detection limit of 5 μM. In addition, the identification of different concentrations of the same tea polyphenols and mixed tea polyphenols have also been achieved. Based on the above study, we further developed a facile and efficient new method for the category differentiation and adulteration identification of green tea, and the accuracy of this array was 96.88% and 100% for eight types of green teas and different adulteration ratios of Biluochun, respectively. This work has significance for the rapid discrimination of green tea brands and adulteration.
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