该研究通过优化提取液pH值、分散固相萃取剂和浓硫酸-甲醇溶液，结合气相色谱质谱法（GC-MS）技术，构建出一种新的、可靠的、用于评估畜肉中14种酸性除草剂残留的分析方法。样品经乙腈提取，调节提取液pH值≤3，使用饱和乙腈的正己烷除脂，通过分散固相萃取剂C18净化，氮气吹干后加入浓硫酸-甲醇溶液衍生化2 min，正己烷提取后通过饱和氯化钠溶剂净化，气相色谱-质谱法EI源测定和基质外标法定量。结果表明，14种酸性除草剂在0.01~0.5 μg/mL范围内线性关系良好，相关系数均大于0.999。本方法检出限为0.001~0.003 mg/kg，定量限为0.003~0.01 mg/kg。空白样品在3个添加水平下（0.01、0.05、0.1 mg/kg）的平均回收率为88.21%~110.0%，相对标准偏差（n=6）为1.02%~8.32%。该方法优势在于衍生时间短，前处理试剂消耗少，方法便捷和灵敏度高，可用于畜肉中14种酸性除草剂残留量的测定。

In this study, a new and reliable analytical method was established for the evaluation of 14 kinds of acidic herbicides residues in livestock meat through optimizing the pH value of the extraction solution, dispersing solid-phase extractant and concentrated sulfuric acid-methanol solution, in combination with gas chromatography-mass spectrometry (GC-MS). The samples were extracted by acetonitrile, the pH of the extraction solution was adjusted to ≤ 3, the fat was removed by n-hexane saturated with acetonitrile, and purified by dispersed solid-phase extractor C18, dried with nitrogen, derivatized by adding concentrated sulfuric acid-methanol solution for 2 min, extracted with n-hexane, t purified by saturated sodium chloride solvent, and determined by EI source-gas chromatography -mass spectrometry and the matrix external standard method. The results showed that the 14 kinds of acid herbicides displayed a good linearity in the concentration range of 0.01~0.5 μg/mL, with all the correlation coefficients being greater than 0.999, the limit of detection in the range of 0.001~0.003 mg/kg and the limit of quantification in the range of 0.003~0.01 mg/kg. At the spiking levels (0.01, 0.05, 0.1 mg/kg), the average recoveries of blank samples were in the range of 88.21%~110.0%, with the relative standard deviations (n=6) ranging between 1.02% and 8.32%. The advantages of this method include short derivatization time, less consumption of pretreatment reagents, convenient method and high sensitivity, which can be used for the determination of 14 kinds of acidic herbicides residues in livestock meat.

国家市场监督管理总局科技计划项目（2022MK072）；山东省药品监督管理局科研项目（SDNMPAFZLS202301）；山东省市场监管局科技项目（SDSJKJ202309）