摘要
应用超高效液相色谱-串联质谱法(ultra-high performance liquid chromatography-tandem mass spectrometry,UPLC-MS/MS)实现发酵面制品的7种甜味剂(糖精钠、甜蜜素、安赛蜜、阿斯巴甜、阿力甜、纽甜、三氯蔗糖)同时检测。样品经机械震荡、超声萃取,亚铁氰化钾溶液和乙酸锌沉淀蛋白,经0.22μm滤膜过滤预处理,以Agilent Eclipse Plus C18柱(2.1 mm×50.0 mm,1.8μm)和乙腈-水为流动相梯度洗脱;电喷雾负离子模式(ESI-)下采用多重反应监测(multiple reaction monitoring,MRM)模式进行分段采集。实验结果:7种甜味剂在0.01~0.50μg/mL浓度范围内线性关系较好,相关系数r^(2)均大于0.9991,检出限为3.0×10^(-6)~3.0×10^(-4)g/kg,定量限为1.0×10^(-5)~1.0×10^(-3)g/kg,样品平均加标回收率为84.5%~96.5%,相对标准偏差为1.3%~8.1%(n=6)。实验结果表明:该方法快速、准确、重现性好,在各种发酵面制品检测中有广泛的应用前景。
This study adopted ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)to detect 7 sweeteners(sodium saccharin,aspartame,acesulfame-K,neotame,alitame,saccharin sodium and chlorinated sucrose)in fermented dough products simultaneously.The samples were pre-treated by mechanical shaking,ultrasonic extraction,precipitation of proteins with ferricyanide potassium and zinc acetate,and filtration through a 0.22μm membrane.The Agilent Eclipse Plus C18 column(2.1 mm×50.0 mm,1.8μm)was washed with a gradient of acetonitrile-water.Multiple reaction monitoring(MRM)mode was used for segmented collection under negativeelectrospray ionization(ESI-).The results showed that the seven sweeteners had good linear relationships within the concentration range of 0.01 to 0.50μg/mL,with correlation coefficients r^(2)greater than 0.9991.The detection limit was 3.0×10^(-6)to 3.0×10^(-4)g/kg and the quantitation limit was 1.0×10^(-5)to 1.0×10^(-3)g/kg.The average recoveries of the samples were 84.5%to 96.5%with relative standard deviations of 1.3%to 8.1%(n=6).The experiment results show that this method is fast,accurate,reproducible,and can be widely applied to the detection of various fermented flour products.
作者
蒋叶灵
侯绪和
吕保樱
JIANG Yeling;HOU Xuhe;LYU Baoying(Guilin Food and Drug Quality Inspection Institute,Guilin 541200,China;Medical School,Guangxi University of Science and Technology,Liuzhou 545005,China)
出处
《广西科技大学学报》
CAS
2023年第3期132-138,共7页
Journal of Guangxi University of Science and Technology
基金
广西科技基地和人才专项(桂科AD19110002)资助。