Classification-Based Evaluation of Multi-Ingredient Dish Using Graphene-Modified Interdigital Electrodes

被引:0
|
作者
Zhu, Hongwu [1 ]
Xu, Yongyuan [1 ]
Liu, Shengkai [1 ]
He, Xuchun [1 ]
Ding, Ning [1 ]
机构
[1] Shenzhen Inst Artificial Intelligence & Robot Soc, Shenzhen 518172, Peoples R China
基金
中国国家自然科学基金;
关键词
electronic tongue; principal component analysis; electrochemical impedance spectroscopy; taste sensors; graphene; TASTE SENSOR; TONGUE; DISCRIMINATION; IDENTIFICATION; NOSE;
D O I
10.3390/mi14081624
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A taste sensor with global selectivity can be used to discriminate taste of foods and provide evaluations. Interfaces that could interact with broad food ingredients are beneficial for data collection. Here, we prepared electrochemically reduced graphene oxide (ERGO)-modified interdigital electrodes. The interfaces of modified electrodes showed good sensitivity towards cooking condiments in mixed multi-ingredients solutions under electrochemical impedance spectroscopy (EIS). A database of EIS of cooking condiments was established. Based on the principal component analysis (PCA), subsets of three taste dimensions were classified, which could distinguish an unknown dish from a standard dish. Further, we demonstrated the effectiveness of the electrodes on a typical dish of scrambled eggs with tomato. Our kind of electronic tongue did not measure the quantitation of each ingredient, instead relying on the database and classification algorithm. This method is facile and offers a universal approach to simultaneously identifying multiple ingredients.
引用
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页数:9
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