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

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.

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。

茶叶是中国主要经济作物之一，而在茶叶种植过程中存在农药不合理使用及滥用等行为，导致茶叶中存在严重农药残留问题。茶叶中农药残留检测主要采用经典化学方法，存在前处理复杂、耗时长、成本高等缺陷，急需研究茶叶中农药残留的快速检测方法，以监管茶叶市场质量安全。项目利用有限元法仿真设计了空气孔形状为矩形的光子晶体光纤的参数，模拟出不同气孔形状光子晶体光纤的模场分布图，按照优化的光子晶体光纤参数，购买了结构相近的空芯光子晶体光纤，采用光纤熔接机放电熔融方法，制作了长度为3cm的光纤，组建了一套基于光子晶体光纤的茶叶痕量农药残留拉曼光谱检测装置，装置测量参数条件达到最优。研制了银纳米增强基底和金纳米增强基底的制备方法，其中金纳米胶底对农药分子的增强效果更好，其稳定性和重现性很好，使用期限可达到6个月。采集了10多种常用农药标准品的拉曼光谱，结合密度泛函理论，对各种农药分子进行结构优化和频率计算，进行谱峰分析和归属；运用波谱学原理、密度泛函理论等方法解析各农残分子振动光谱的相应谱带归属，确定各农药分子的特征谱峰，建立各农残分子特征信息数据库。探索了PSA、NH2、C18、Fe3O4、GCB和NBC对茶叶中基质效应的影响，对影响绿茶叶基质效应的净化材料、净化剂用量进行优化选择，建立了简单快速提取含农药残留茶叶提取液的前处理方法。确定了定性定量分析茶叶中农药残留的特征谱峰，建立了SERS结合快速前处理方法分析茶叶中乐果、噻菌灵、毒死蜱、苯醚甲环唑等农药残留的快速检测方法。探讨了化学计量学方法优选茶叶中多个农药特征变量的可行性，建立了化学计量学方法结合SERS快速检测茶叶中苯醚甲环唑和毒死蜱农药残留的方法，优选出多个有关农药特征谱峰建立定量分析模型，提高了方法的检测精度和灵敏度；方法对农药的检出限达到5ppm以下，检测精密度达到20%，单个样品检测时间不多于15分钟。研究结果可为茶叶中农药残留质量安全市场监管及出入境检测提供了一种新的方法。