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基于分类的多成分菜肴评估:使用石墨烯修饰叉指电极

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

作者信息

Zhu Hongwu, Xu Yongyuan, Liu Shengkai, He Xuchun, Ding Ning

机构信息

Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), Shenzhen 518172, China.

出版信息

Micromachines (Basel). 2023 Aug 17;14(8):1624. doi: 10.3390/mi14081624.

Abstract

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.

摘要

一种具有全局选择性的味觉传感器可用于辨别食物的味道并提供评价。能够与多种食品成分相互作用的界面有利于数据收集。在此,我们制备了电化学还原氧化石墨烯(ERGO)修饰的叉指电极。在电化学阻抗谱(EIS)下,修饰电极的界面在混合多成分溶液中对烹饪调味品表现出良好的灵敏度。建立了烹饪调味品的EIS数据库。基于主成分分析(PCA),对三个味觉维度的子集进行了分类,这可以将未知菜肴与标准菜肴区分开来。此外,我们在一道典型的番茄炒鸡蛋菜肴上展示了电极的有效性。我们这种电子舌并不测量每种成分的定量,而是依赖于数据库和分类算法。该方法简便易行,为同时识别多种成分提供了一种通用方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4e5/10456818/bfdceca5d7e2/micromachines-14-01624-g001.jpg

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