基于智能手机及机器学习技术对食品中多种抗生素的识别

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

基于铬黑T与铕离子构建了比色和荧光双通道探针(EBT/Eu^(3+)),利用智能手机颜色识别和荧光测试获得四种四环素加入EBT/Eu^(3+)后颜色和荧光信号的变化,结合机器学习中模式识别方法,成功实现了蜂蜜中四种四环素的识别。本实验将探针制备、智能手机颜色获取、荧光测试、机器学习、多种抗生素识别等多个知识点进行创新融合,综合性强。

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 two-channel probe preparation,color recognition based on smart phone,fluorescence measurements,machine learning,and identification of various antibiotics.