高效液相色谱-串联质谱法测定植物性食品中多种有机锡化合物
Determination a Variety of Organotin Compounds in Foodstuffs of Plant Origin by High Performance Liquid Chromatography-Tandem Mass Spectrometry
石声鑫 1杨建英 1徐宁 1陈晓红 1陈庆 1肖晓槟1
作者信息
- 1. 广东省汕头市质量计量监督检测所,广东 汕头 515041
- 折叠
摘要
样品分别经甲酸乙腈(甲酸 1%)和甲酸甲醇(甲酸 1%)提取,上清提取液经混合盐析试剂除水分层,上清液与水按 2∶3(体积比)混合,过膜后上机检测.以 0.2 g·L-1 乙酸铵水溶液(含 0.1%甲酸)-0.1%甲酸乙腈为流动相,在 0.3 mL·min-1 流速下梯度洗脱,采用苯基色谱柱进行液相分离,正离子模式检测,外标法定量.结果表明,在草莓、苹果、柑橘、葡萄、黄瓜 5 种基质中,7 种有机锡化合物线性关系良好,相关系数均≥0.995;方法检出限为 0.2～4 μg·kg-1,定量下限为 0.5～10 μg·kg-1;在 3 个浓度添加水平下,7 种有机锡化合物的平均回收率为 68.1%～103.1%,相对标准偏差为 1.00%～11.36%.该方法准确、灵敏、快捷,适用于植物源性食品中多种有机锡化合物的定量分析.
Abstract
The samples were extracted with formic acid acetonitrile(1%formic acid)and formic acid methanol(1%formic acid),respectively.The supernatant extract was dehydrated and layered using a mixed salt precipitation reagent.The supernatant was mixed with water in a ratio of 2∶3(volume ratio),and then subjected to membrane filtration and machine detection.Using 0.2 g·L-1 ammonium acetate aqueous solution(containing 0.1%formic acid)-0.1%formic acid acetonitrile as the mobile phase,gradient elution was performed at a flow rate of 0.3 mL·min-1.A benzene chromatography column was used for liquid phase separation,positive ion mode detection,and external standard quantification.The results showed that among the five substrates of strawberries,apples,citrus,grapes,and cucumbers,seven organic tin compounds had a good linear relationship,with correlation coefficients≥0.995;the detection limit of the method is 0.2～4 μg·kg-1,lower limit of quantification is 0.5～10 μg·kg-1;at three levels of concentration addition,the average recovery rates of seven organotin compounds were 68.1%～103.1%,with a relative standard deviation of 1.00%to 11.36%.This method is accurate,sensitive,and fast,and is suitable for quantitative analysis of various organic tin compounds in plant-based foods.
关键词
高效液相色谱-串联质谱法/有机锡化合物/植物性食品Key words
high performance liquid chromatography-tandem mass spectrometry/organotin compounds/foodstuffs of plant origin引用本文复制引用
基金项目
广东省市场监督管理局2023年度科技项目(2023CS09)
出版年
2024
NETL
NSTL
万方数据