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

作　　者：邓松泉 龚琪 唐艳秋 王楠[1] 陈芳[1] 朱丽华[1] 王靖宇[1] 王宏[1] Songquan Deng;Qi Gong;Yanqiu Tang;Nan Wang;Fang Cheng;Lihua Zhu;Jingyu Wang;Hong Wang(School of Chemistry and Chemical Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学化学与化工学院,武汉430074

出　　处：《大学化学》2023年第8期177-185,共9页University Chemistry

基　　金：华中科技大学教学研究项目(2021109)。

摘　　要：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.

关 键 词：铬黑T 铕离子 比色荧光探针 模式识别 抗生素 

分 类 号：G64[文化科学—高等教育学] O6[文化科学—教育学]