期刊文献+

表面增强拉曼技术在中药污染物检测中的应用与展望 被引量:4

Recent advances in surface-enhanced Raman scattering technique for pollutant detection in Chinese medicinal material
原文传递
导出
摘要 中药材是中医药行业的基础,中药材质量问题关乎居民健康生活和国家中医药行业的发展。农药残留、重金属、真菌毒素等是影响中药材质量的主要因素。目前,应用于污染物快速检测的方法层出不穷,表面增强拉曼光谱技术因其快速、无损的优点已在食品化学、环境分析等领域广泛应用,在中药污染物检测领域同样表现出巨大潜力。该文将回顾表面增强拉曼光谱技术在中药常见污染物的检测应用,重点讨论其用于农药残留检测的特点和优势,包括检测原理、基底设计、农药特异性识别等方面,为中药中多农药残留快速检测提供思路。 Chinese medicinal material is the foundation of traditional Chinese medicine(TCM)industry.Its quality is not only closely related to the health of residents but also the key to the development of the TCM industry.Pesticide residues,heavy metals and mycotoxins are the major pollutants of Chinese medicinal materials.In recent years,quite a number of rapid detection methods for pollutants have been constructed.Among them,surface-enhanced Raman scattering(SERS),which has been widely used in food chemistry,environmental analysis,and other fields because of its speediness and non-destructiveness,shows its great potential in the pollutant detection in Chinese medicinal material.This paper firstly reviews the application of SERS for the detection of common pollutants in Chinese medicinal material.We then discussed the characteristics and advantages of SERS technique for pesticide detection,including the principle,SERS substrate design,specific recognition,etc.Finally,simultaneous detection of multiple pesticide residues in Chinese medicinal material was explored.
作者 王婷 魏金超 王一涛 李鹏 WANG Ting;WEI Jin-chao;WANG Yi-tao;LI Peng(State Key Laboratory of Quality Research in Traditional Chinese Medicine,Institute of Chinese Medical Sciences,University of Macao,Macao 999078,China;Institute of Traditional Chinese Medicine&Natural Products,College of Pharmacy,Jinan University,Guangzhou 510632,China)
出处 《中国中药杂志》 CAS CSCD 北大核心 2021年第1期62-71,共10页 China Journal of Chinese Materia Medica
基金 澳门科技发展基金项目(162/2017/A3) 国家自然科学基金项目(81903794)。
关键词 中药 质量控制 污染物 农药残留 拉曼 快速检测 综述 Chinese medicinal material quality control pollutant pesticide residue Raman rapid detection review
  • 相关文献

参考文献17

二级参考文献222

共引文献311

同被引文献59

引证文献4

二级引证文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部