有机磷、有机硫和烟碱类农药常应用于叶菜的种植和生产中，常规的检测方法前处理复杂、检测时间长、成本高等特点，难以满足快速检测的需求，为了实现农药残留的在线检测，本文提出一个基于SERS技术进行定量和定性分析叶菜中农药残留的检测方法，选取农药的特征拉曼峰作为校正峰，制定农药残留的浓度与校正峰强度的线性校准方程，将最低检测限对应SERS光谱的校正峰的强度代入线性校准方程，计算出定量检测限。研究表明，小白菜中亚胺硫磷农药的检测限能达到0.5 mg/kg以下，相关系数R2为0.95273，标准偏差为2.89%~13.63%，回收率为96.00%~121.33%；大白菜中福美双农药残留的检测限能达到0.5 mg/kg以下，相关系数R2为0.8905，标准偏差为3.90%~8.39%，回收率为88.80%~112.44%；空心菜中啶虫脒农药残留的检测限能达到1 mg/kg以下，相关系数R2为0.93858，标准偏差为2.12%~9.29%，回收率为87.67%~107.17%。这些结果说明，基于SERS技术进行定量和定性分析叶菜中农药残留的检测方法是一种有效的方法，可以实现叶菜农药残留的快速无损检测。

Three kinds of pesticides, organic phosphorus, organosulfur and neonicotinoids were used widely in the cultivation and production of leaf vegetables. The chromatographic methods are difficult to realize in situ detection. In this work, a surface-enhanced Raman scattering (SERS) approach for qualitative and quantitative detection pesticide residues in leaf vegetables was developed. The characteristic Raman peaks of pesticides were selected as correction peaks. The linear calibration equations were established with pesticide residues concentration and correction peak intensity. The limit of quantitation (LOQ) was calculated by substituting the correction peak intensity of SERS spectrum corresponding to the limit of detection (LOD) into the linear calibration equation. The results showed that the LOD for phosmet residues in pakchoi reached below 0.5 mg/kg with the correction Raman peak of 604 cm-1, and the correlation coefficient R2 was 0.95273, and the standard deviation (SD) was 2.89%~13.63%, the recovery rate was 96.00%~121.33%. The LOD for thiram residues in Chinese cabbage reached below 0.5 mg/kg with the correction Raman peak of 1385 cm-1, and R2 was 0.8905, and SD was 3.90%~8.39%, the recovery rate was 88.80%~112.44%. The LOD for acetamiprid residues in swamp cabbage reached below 1 mg/kg with the correction Raman peak of 1111 cm-1, and R2 was 0.93858, and SD was 2.12%~9.29%, the recovery rate was 87.67%~107.17%. These showed that the SERS method might be an effective method for the rapid and reliable detection of pesticide residues in leaf vegetables.

国家自然科学基金项目（31460419；61562039）；江西省教育厅科学技术研究项目（GJJ170270）；江西省教育厅科学技术研究重点项目（GJJ170246）