基于深共晶溶剂的液-液微萃取法结合液相色谱-串联质谱法检测枸杞中的10种农药残留

Determination of 10 kinds of pesticide residues in wolfberry by liquid-liquid micro-extraction method with deep eutectic solvent combined with liquid chromatography-tandem mass spectrometry

中文关键词:  深共晶溶剂  枸杞  农药残留  液相色谱-串联质谱法

英文关键词:deep eutectic solvent  wolfberry  pesticide residue  liquid chromatography-tandem mass spectrometry

中文摘要:

      目的 建立基于深共晶溶剂的液-液微萃取结合液相色谱-串联质谱法检测枸杞中10种农药多残留的分析方法。方法 通过氢键供体和受体的组成及合成比例、深共晶溶剂的密度、粘度和傅里叶红外光谱分析对深共晶溶剂进行优化表征。在50 ℃恒温条件下, 分别以深共晶溶剂为萃取剂, 四氢呋喃为乳化剂, 通过涡旋和超声进行提取。离心后实现两相分离, 下层深共晶溶剂相用甲醇-水(50:50, V:V)稀释上样。结果 目标物在0.01~50.0 μg/kg范围内线性关系良好, 线性相关系数均大于0.9997, 方法的检出限和定量限分别为0.0088~0.5952 μg/kg和0.0294~1.9814 μg/kg。在3个加标水平(0.2、2.0、20.0 μg/kg)下, 10种农药的回收率分别为79.8%~99.4%, 82.3%~101.8%和88.5%~102.4%, 相对标准偏差均小于15.0%, 符合多农药残留检测要求。结论 该方法操作简单、准确度高, 适用于枸杞中农药残留等污染物的检测。

英文摘要:

      Objective To establish a method for determination of 10 kinds of pesticide residues in wolfberry by liquid-liquid micro-extraction method based on deep eutectic solvents combined with liquid chromatography-tandem mass spectrometry. Methods The deep eutectic solvents were optimized and characterized by the composition and synthesis ratio of hydrogen bond donors and acceptors, the density and viscosity of the deep eutectic solvents, and fourier transform infrared spectroscopy. At a constant temperature of 50 ℃, the deep eutectic solvent was used as the extractant and tetrahydrofuran was used as the emulsifier. The extraction was carried out by vortex and ultrasound. The two-phase separation was realized after centrifugation. The lower deep eutectic solvent phase was diluted with methanol water (50:50, V:V). Results The linear relationship of the targets were good in the range of 0.01-50.0 μg/kg, and the linear correlation coefficients were greater than 0.9997. The limits of detection and limits of quantitative of the method were 0.0088?0.5952 μg/kg and 0.0294?1.9814 μg/kg, respectively. The recoveries of 10 pesticides at 3 fortification levels (0.2, 2.0, 20.0 μg/kg) were 79.8%?99.4%, 82.3%?101.8% and 88.5%?102.4%, respectively. The relative standard deviations were all less than 15.0%, which met the requirements of pesticide residue detection. Conclusion This method is simple and accurate, and is suitable for the determination of pesticide residues and other pollutants in wolfberry.