纳米材料比色分析传感器在食品检测中的应用进展

doi:10.16085/j.issn.1000-6613.2017.01.003

摘要/Abstract

摘要： 近年来食品检测作为食品安全的重要保障而备受关注，特别是简便、灵敏、准确的食品检测手段和方法已成为研究热点。本文简述了食品分析的基本内容和检测方法，在阐述基于模拟酶纳米材料和纳米粒子的两类比色分析传感器构建原理的基础上，介绍了两类纳米材料比色分析传感器在食品添加剂和生物毒素、化学毒素等食品污染物检测中的应用，特别对金属离子、农/兽药残留和非法添加物等化学毒素的检测进行了回顾，最后对基于纳米材料比色分析传感器的发展趋势进行了展望。纳米比色分析传感器可通过溶液颜色变化直观地检测食品中的各类物质，具有灵敏度高、响应快速和易微型化等优点，未来该类传感器应加强与生物复合材料的结合，在实现检测快速化、精准化的同时提高传感器的稳定性。

关键词: 金银纳米粒子, 纳米材料模拟酶, 比色分析传感器, 食品检测

Abstract: Food testing as an important guarantee of food safety has attracted much attention in recent years. Especially,with simple,sensitive and accurate means and methods of food testing,it has been one of hot research topics. In this paper,basic content and testing method of food analysis were described. Furthermore,on the basis of introducing construction principle of two kinds of colorimetric sensor based on nanomaterials with enzyme activity and nanoparticles,the applications of those nanomaterials colorimetric sensors in food additives as well as biotoxin,chemical toxin and other contaminants detection were summarized,especially for metal ions,agricultural/veterinary drug residues and illegal additives and other chemical toxins. Finally,the development trends for colorimetric sensor in the future were prospected. Nano colorimetric sensors could visually detect various types of substances in food by the color changing of solution,which had high sensitivity,rapid response and amenable miniaturization advantages. In the future,these sensors should be strengthened in conjunction with such biocomposites and improved the stability,while achieved rapid and precision detection technology.

Key words: gold and silver nanoparticles, mimic enzyme nanomaterials, colorimetric sensors, food testing

中图分类号:

O652

吕佳, 张浩春, 张冰, 高文超, 李兴, 常宏宏, 魏文珑. 纳米材料比色分析传感器在食品检测中的应用进展[J]. 化工进展, 2017, 36(01): 20-28.

LÜ Jia, ZHANG Haochun, ZHANG Bing, GAO Wenchao, LI Xing, CHANG Honghong, WEI Wenlong. Application of colorimetric sensor based nanomaterials in food detection[J]. Chemical Industry and Engineering Progree, 2017, 36(01): 20-28.

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