Improved matrix purification using a graphene oxide-coated melamine sponge for UPLC-MS/MS-based determination of 37 veterinary drugs in milks

Xu Xu, Jia Lv, Jintian Zhou,Baocheng Ji,Lanrui Yang,Gaigai Xu, Zhuchen Hou, Lulu Li,Yanhong Bai

Analytical methods : advancing methods and applications(2024)

引用 0|浏览1
暂无评分
摘要
A rapid and highly sensitive method was established for the analysis of 37 veterinary drug residues in milk using a modified QuEChERS method based on a reduced graphene oxide-coated melamine sponge (rGO@MeS) coupled with UPLC-MS/MS. Under optimal chromatographic and mass spectrometric conditions, the effects of different dehydrated salts (MgSO4 and Na2SO4) and metal chelating agents (Na2EDTA) on extraction efficiency were first investigated. Next, the influence of a dynamic and static purification mode was evaluated in terms of drug recoveries. Calibration curves of 37 veterinary drugs were constructed in the range 0.6-500 mu g kg-1, and good linearities were obtained with all determination coefficients (R2) >= 0.992. The limits of detection (LODs) and quantitation (LOQs) were in the range 0.3-1.1 mu g kg-1 and 0.6-3.5 mu g kg-1, respectively. The recoveries of all compounds were in the range 61.3-118.2% at three spiked levels (20, 100, and 200 mu g kg-1) with RSDs <= 15.4% for both intra- and inter-day precisions. Compared to pristine melamine sponges and commercial adsorbents (C18, PSA, and GCB), rGO@MeS demonstrated an equal or even better purification performance in terms of recoveries, matrix effects, and matrix removal efficiency. This method is rapid, simple, efficient, and appropriate for the qualitative and quantitative analyses of 37 veterinary drug residues in milk, providing a new detection strategy and technical support for the routine analysis of animal-derived food. A fast and convenient matrix purification method based on a reduced graphene oxide coated melamine sponge was developed for the analysis of 37 veterinary drugs in milks using UPLC-MS/MS.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要