摘要
建立了增强型脂质去除固相萃取-液相色谱串联质谱法测定畜禽产品中的泰万菌素和3-O-乙酰泰乐菌素残留量。通过比较多种类型固相萃取柱对泰万菌素和其代谢物3-O-乙酰泰乐菌素测定结果的影响,最终选用甲酸-乙腈-水溶液提取,Captiva EMR-Lipid柱净化。利用单因素实验优化了乙腈-水体积比、甲酸含量以及振荡提取时间等影响因素,并在此基础上进行L9 (3~3)正交实验。通过方差分析明确主次因素,确定各因素之间最佳组合方式为:采用0.3%甲酸-乙腈-水溶液(90/10, V/V)提取,振荡25 min,Captiva EMR-Lipid柱净化。结果显示,泰万菌素和3-O-乙酰泰乐菌素在0.2~10μg/L线性范围内线性关系良好,线性相关系数R>0.998。在1, 5, 10, 50μg/kg加标水平下,平均回收率为76.5%~93.5%,相对标准偏差为1.6%~7.3%。
An enhanced lipid removal solid phase extraction-liquid chromatography tandem mass spectrometry method was developed for the determination of residues of tylvalosin and 3-O-acetyltylosin in livestock and poultry products.The effects of different types of solid phase extraction columns on the determination results of tylvalosin and its metabolite 3-O-acetyltylosin were compared.Formic acid-acetonitrile-water solution was used for extraction,and Captiva EMR-Lipid column was used for purification.The volume ratio of acetonitrile to water,the content of formic acid and the extraction time of vibration were respectively optimized by single factor experiments.Based on this,the L9(3^(3))orthogonal experiment was carried out.The primary and secondary factors were identified by variance analysis.The best combination of these factors were as followed:extracted with 0.3%formic acid-acetonitrile-water solution(90/10,V/V),vibrated for 25 min,and purified the lipid with Captiva EMR-Lipid column.The results showed that tylvalosin and 3-O-acetyltylosin had good linear relationships in the range of 0.2-10μg/L,with the correlation coefficients of R>0.998.The average recoveries were 76.5%to 93.5%at the spiked levels of 1,5,10 and 50μg/kg,and the relative standard deviations were 1.6%-7.3%.
作者
陈彦宏
王宇
钟玉心
赵金利
何咏欣
龚海锟
杨嘉鑫威
钱振杰
CHEN Yanhong;WANG Yu;ZHONG Yuxin;ZHAO Jinli;HE Yongxin;GONG Haikun;YANG Jiaxinwei;QIAN Zhenjie(Guangzhou Institute for Food Inspection,Guangzhou 511400,China;Party School of the Guangdong Provincial Committee of CPC,Guangzhou 510000,China)
出处
《分析试验室》
EI
CAS
CSCD
北大核心
2024年第8期1159-1164,共6页
Chinese Journal of Analysis Laboratory
基金
广东省自然科学基金项目(2019B1515210025)
广州市市场监督管理局科技项目(2022kj36)资助。
