建立了超高效液相色谱-串联质谱法快速筛查减肥、抗疲劳和增强免疫力类保健食品中非法添加78种化学药物的方法。保健食品样品经甲醇溶剂提取、QuEChERS净化，试样以C18柱分离，多反应监测（MRM）模式进行定量与定性分析，采用外标法定量。采用ACQUITY UPLC HSS T3柱（2.1×100 mm，1.7 μm）进行分离，以乙腈和乙酸铵溶液（含0.1%甲酸）作为流动相，进行梯度洗脱,质谱采用正离子和负离子同时扫描分析。在优化的色谱、质谱条件下，78种化学药物能够得到较好分离，在线性范围内线性关系良好，相关系数均大于0.9991，检出限（LOQ）为0.5 μg/kg~420 μg/kg。各组分在三个不同加标水平下平均回收率为59.9%~120.7%，相对标准偏差（RSD）为1.3%~16.2%。运用本方法对57批次保健食品进行快速筛查，检出41批次样品含有一种或多种非法添加药物,被检出的药物为西布曲明、苄基西布曲明、氯代西布曲明、酚酞、伪麻黄碱、麻黄碱、二甲双胍、咖啡因、茶碱、番泻苷A、番泻苷B、呋塞米、大黄素和西地那非。本方法样品处理过程简单，分析时间短，准确可靠，灵敏度高，适用于保健食品中非法添加化学药物的定性与定量检测及快速筛查。

A method was developed for the determination of 78 chemical drugs illegally added in three types of health foods (slimming, anti-fatigue and sexual promoting health foods) by QuEChERS--ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The samples were extracted with methanol. The extracted solution was purified with QuEChERS approach. The seventy eight chemical drugs were then separated on a ACQUITY UPLC HSS T3 column (2.1×100 mm, 1.7 μm) through gradient elution with acetonitrile and 10 mmol/L of ammonium acetatesolution (0.1% formic acid) using as mobile phase and detected by MS/MS under multi-reactions monitoring (MRM) modes (ESI+ and ESI-)). The chemical drugswere quantified with external standard method. Under the optimal conditions, these chemical drugs were well separated, and had good linear relationship (r≥0.9991). The limits of detection (LOD) (S/N≥3) were 0.5 μg/kg~420 μg/kg. The average recoveries at three spiked levels were in the range of 59.9%~120.7%, with the relative standard deviation (RSD, n=3) of 1.3%~16.2%. This newly developed method was successfully applied for the determination of 57 health food samples, in which 14 chemical drugs were found in 41 samples. The developed method is rapid, simple, sensitive and highly efficient which can be used for the qualitative and quantitative determination of illegally added chemical drugs in the slimming, anti-fatigue and sexual promoting health foods.

广东省自然科学基金项目（2017A030313218；2020A1515011308）；中山市社会公益重大专项（2018B1025）；电子科技大学中山学院教学团队项目（JXTD201901）