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

Author:

Zhu Hongwu1ORCID,Xu Yongyuan1,Liu Shengkai1,He Xuchun1,Ding Ning1

Affiliation:

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

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.

Funder

Shenzhen Science and Technology Program

National Key R&D Program of China

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

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