摘要
本文采用QuEChERS前处理法,结合LC-MS/MS,开发氟咯草酮在马铃薯田间生态系统中的样品前处理和残留快速分析方法。样品用乙腈提取,用PSA净化,含有0.02%(v/v)乙酸的甲醇/水和5 mmol乙酸铵的组合作为流动相,Shim-pack XR-ODSII色谱柱分离,三重四级杆电喷雾多反应检测模式进行检测。结果表明,在0.01-1.00mg/L范围内,氟咯草酮溶剂标准曲线和基质标准曲线有良好的线性关系,R^(2)均大于0.9990。在0.01mg/kg、0.10mg/kg、1.00mg/kg的添加水平下,氟咯草酮在马铃薯各基质中日内平均回收率分别为79.1%-91.6%、80.1%-89.5%和80.7%-90.0%,相对标准偏差分别在0.9%-4.3%、0.9%-4.1%和1.5%-3.6%之间;日间平均回收率为78.7%-91.6%,相对标准偏差在0.7%-4.3%之间。此方法简便、快捷、灵敏度高,适用于氟咯草酮在马铃薯田间各种基质中的残留检测。
In this paper,the QuEChERS pretreatment method,combined with LC-MS/MS,was used to develop a sample pretreatment and residue rapid analysis method for flurochloridone in the potato field ecosystem.The sample was extracted with acetonitrile and purified with PSA.A combination of methanol/water containing 0.02%(v/v)acetic acid and 5 mmol ammonium acetate was used as the mobile phase.Shim-pack XR-ODSII chromatographic column separation,triple quadrupole electrospray Reaction detection mode for detection.The results showed that in the range of 0.01-1.00 mg/L,the standard curve of flurochloridone solvent and the standard curve of matrix had a good linear relationship,and R2 was both greater than 0.9990.At the addition level of 0.01mg/kg,0.10mg/kg,1.00 mg/kg,the average daily recovery rates of flurochloridone in the potato substrates were 79.1%-91.6%,80.1%-89.5-%and 80.7%-90.0%,respectively,relative to the standard The deviations were between 0.9%-4.3%,0.9%-4.1%,and 1.5%-3.6%;the average daily recovery rate was 78.7%-91.6%,and the relative standard deviation was between 0.7%-4.3%.This method is simple,fast,and highly sensitive,and is suitable for the detection of flurochloridone residues in various substrates in potato fields.
作者
李宗兴
李玮
LI Zong-xing;LI Wei(College of Agriculture and Animal Husbandry,Qinghai University,Xining Qinghai 810016,China;Academy of Agriculture and Forestry,Qinghai University,Xining Qinghai 810016,China;Provincial Key Laboratory of Agricultural Integrated Pest Management of Qinghai,Xining Qinghai 810016,China)
出处
《青海农林科技》
2021年第4期18-22,29,共6页
Science and Technology of Qinghai Agriculture and Forestry
基金
青海大学农牧学院科研训练项目(NKX 201924)。
