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Citation: Songquan Deng, Qi Gong, Yanqiu Tang, Nan Wang, Fang Cheng, Lihua Zhu, Jingyu Wang, Hong Wang. Smart Phone Coupled with Machine Learning for Identifying Multiple Antibiotics in Food[J]. University Chemistry, ;2023, 38(8): 177-185. doi: 10.3866/PKU.DXHX202208135 shu

Smart Phone Coupled with Machine Learning for Identifying Multiple Antibiotics in Food

School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Corresponding author: Hong Wang, hongwzy@hust.edu.cn
Received Date: 31 August 2022

In this study, a method for identifying residual antibiotics in food was developed based on chromium black T and europium ion as colorimetric and fluorescent probes (EBT/Eu³⁺) coupled with pattern recognition in machine learning. The changes in color and fluorescence of four antibiotics with the addition of EBT/Eu³⁺ were obtained using smart phone and fluorescence measurements. Assisted by pattern recognition, the four antibiotics in honey were successfully identified. This experiment is highly comprehensive; it integrates multiple knowledge points, such as two-channel probe preparation, color recognition based on smart phone, fluorescence measurements, machine learning, and identification of various antibiotics.
- Chromium black T,
- Europium ion,
- Colorimetric and fluorescent probe,
- Pattern recognition,
- Antibiotics
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