基于光子晶体光纤的茶叶痕量农药残留表面增强拉曼光谱检测研究

项目名称： 基于光子晶体光纤的茶叶痕量农药残留表面增强拉曼光谱检测研究

项目编号： No.31460315

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 农业科学

项目作者： 吴瑞梅

作者单位： 江西农业大学

项目金额： 45万元

中文摘要： 前期利用表面增强拉曼光谱（SERS）检测干茶叶农药残留，发现痕量农药的拉曼峰受茶叶基体干扰大，达不到国家检测要求。拟采用基于光子晶体光纤的表面增强拉曼光谱技术来增强痕量农药分子的拉曼效应，以增强谱峰强度，提高检测灵敏度。 项目拟选择前期研究干茶叶中5种农药为对象，采用茶叶实际培育方法制备含不同浓度农药的干茶样品。设计光子晶体光纤结构，优化基于光子晶体光纤的拉曼检测装置，获取干茶叶的SERS。探索简单、快速提取含农残茶叶提取液的前处理方法。结合化学方法测定值，研究农药分子谱峰强度的影响因素，解析采用本方法增强的农药分子拉曼特征信号，确定各农残分子的定性定量谱峰。研究农残的SERS定性定量分析方法，考察农药浓度与拉曼响应之间的关系，确定最低检测限，建立定量检测模型。 项目拟建立完善的茶叶痕量农药的光子晶体光纤表面增强拉曼光谱检测方法，为茶叶农药残留实时快速检测装置和分析方法的开发提供技术支持。

中文关键词： 茶叶；痕量农药残留；光子晶体光纤；表面增强拉曼光谱

英文摘要： The early study on detecting the trace pesticide residual in tea using surface enhanced raman spectroscopy demonstrated that the intensity of Raman spectra of trace pesticide was affected by the complex matrix information in tea and the precision of this method could not reach the trace detection requirements. In this project, a new method of combining the photonic crystal fiber (PCF) with surface enhanced Raman spectroscopy will be used to enhance the raman effect of trace pesticide molecule, enhance their peak strength and improve the detection sensitivity. Five comon pesticides studied in our early study is regard as the object for this research. Dry tea samples with different concentration pesticides are made by tea practical cultivation method. Photonic crystal fiber is designed, and then a new raman detection device is established based on photonic crystal fiber in our laboratory. The raman spectroscopy of tea containing pesticide residues are collected in this detection device. The pre-treatment method for simply and fast extracting the trace pesticide residual in tea is explored. Combined with the Chemical measurements, factors affecting the peak intensity of pesticide molecules are studied, the enhanced raman characteristic peak signals of pesticide molecule are analyzed based on the results of the chemical analysis experimental method. The qualitative and quantitative spectral peaks of each pesticide molecule are confirmed. The relationship between pesticide concentration and raman response is investigated and the lowest detection limit is determined. A quantitative detection model for analyzing pesticide concentration is built. Finally, a thorough detection method of trace pesticide residues in tea based on surface enhanced raman spectroscopy combined with photonic crystal fiber is established, which will provide technical support for the development of a rapid, real-time detection device and analytical method for trace pesticide residues in tea.

英文关键词： tea;trace pesticide residues;photonic crystal fiber;surface enhanced raman spectroscopy