摘要
建立了基于多反应监测模式下的超高效液相色谱-串联质谱法对减肥类保健食品中西布曲明等6种典型违禁药物快速筛查方法。样品经1%甲酸-甲醇溶液提取,超声波水浴20 min助提,以Hypersil GOLD C18为分离柱,0.1%甲酸-水和甲醇为流动相,梯度洗脱程序,经超高效液相色谱-质谱联用仪在多反应监测模式(MRM)下进行分析。采用该方法,6种违禁药物总分析时长仅为8 min,各组分离子色谱图峰型良好,保留时间在2.188~5.119 min之间,各组分在0.5~100μg/L的线性范围内相关系数(R^(2))均大于0.99,检出限为0.5~1.0μg/kg,定量限为1.4~3.5μg/kg,低、中、高三个加标质量分数(20,100和500μg/kg)下平均回收率为78.1%~99.3%,SRSD为3.6%~8.8%。该方法具有操作简便、仪器维护成本低、分析快速、回收率高、基质干扰小等优点,能够充分满足当下检测实验室多批次、高通量、多组分检验的需求。
Established a rapid screening method for 6 typical prohibit drugs including sibutramine in diet health food based on ultra-high performance liquid chromatography-multiple reaction monitoring mass spectrometry.The samples were extracted with 1%formic acid-methanol solution,and assisted by ultrasonic water bath for 20 min.Hypersil GOLD C18 was used as separation column.0.1%formic acid-water and methanol were used as mobile phases,gradient elution procedure,and analyzed by UPLC-MS/MS in multiple reaction monitoring mode(MRM).Using this method,the 6 prohibit drugs were analyzed in only 8 mins,the peak shape of each component ion chromatogram was good,and the retention time was between 2.188 and 5.119 min.The correlation coefficient(R^(2))of each component in the linear range of 0.5-100μg/L was greater than 0.99,the limit of detection was 0.5-1.0μg/kg,then the limit of quantification was 1.4-3.5μg/kg.Meanwhile,the average recoveries at the spiked concentrations(20,100 and 500μg/kg)were 78.1%-99.3%,and the SRSD was 3.6%-8.8%.This method had the advantages of simple operation,low instrument maintenance cost,rapid analysis,high recovery rate,and low matrix interference,which could fully meet the needs of current testing laboratories for multi-batch,high-throughput,and multi-component testing.
作者
韩瑨烜
寇雷
李勇
万玉炜
HAN Jinxuan;KOU Lei;LI Yong;WAN Yuwei(Xinjiang Uygur Autonomous Region Product Quality Supervision and Inspection Institute,Urumqi 830011;Xinjiang Vocational University,Urumqi 830011)
出处
《食品工业》
CAS
2022年第7期303-306,共4页
The Food Industry
基金
自治区创新环境(人才、基地)建设专项(PT2106)
自治区区域协同专项(上海合作组织科技伙伴计划及国际科技合作计划)项目(2020E01051)。