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

Abstract

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/Eu 3+ ) coupled with pattern recognition in machine learning. The changes in color and fluorescence of four antibiotics with the addition of EBT/Eu 3+ 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 twochannel probe preparation, color recognition based on smart phone, fluorescence measurements, machine learning, and identification of various antibiotics.