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基于磁纳米材料的土壤中多农药残留高通量分析技术研究
High Throughput Analysis of Multiple Pesticides Residue in Soil Samples Using Magnetic Nanoparticles as Dispersive Adsorbent
【摘要】 建立了土壤中43种农药及代谢物残留的高通量分析方法。土壤样品经乙腈超声萃取后,采用分散固相萃取法进一步对萃取液进行净化。选择修饰N-丙基乙二胺(PSA)的Fe3O4磁纳米材料和C18为分散净化吸附剂,采用超高效液相色谱-串联质谱(UPLC-MS/MS)分析。优化实验结果表明,超声萃取时间为10 min、净化吸附剂Fe3O4-PSA用量为40 mg、C18用量为30 mg时,农药的回收率最佳。除3-羟基克百威和水胺硫磷(5~250μg/L)外,各农药在2~250μg/L范围内呈良好线性关系,相关系数(R)均大于0.9700,检出限为0.1~1.0μg/L。在10、100和200μg/kg的添加浓度下,目标分析物在土壤中的回收率在74.1%~120.0%之间,相对标准偏差≤18.1%。本方法前处理过程简单,灵敏度高,净化效果好,适用于土壤中多农药残留分析。
【Abstract】 A simple and rapid sample pretreatment method was developed based on magnetic nanoparticles for multi-pesticides residue analysis in soil samples. The target analytes were extracted by acetonitrile under the assistance of ultra-sonication,followed by the purification of dispersive solid phase extraction. The magnetite(Fe3O4) nanoparticles modified with 3- (N,N-diethylamino) propyltrimethoxysilane (Fe3O4-PSA) and commercial C18 were selected as the cleanup adsorbents to remove the matrix interferences. The target analytes were further analyzed by ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLCMS/MS). The factors influencing the recoveries of analytes,such as extraction time,amount of Fe3O4-PSA and C18,were optimized. The optimal extraction time was 10 min,and the amount of Fe3O4-PSA and C18 were 40 mg and 30 mg,respectively. The method showed good linearity in the concentration range from 2 μg/L to 250 μg/L except for 3-hydroxy-carbofuran and isocarbophos (5 μg/L to 250 μg/L). The limits of detection(LODs) ranged from 0.1 μg/L to 1.0 μg/L. The recoveries ranged from 74.1% to 120.0% at three spiked concentration levels with relative standard deviations of lower than 18.1%. The proposed method was rapid,simple,low-cost and effective for detection of trace multi-pesticides residue in soil.
【Key words】 Soil; Magnetic dispersive solid phase extraction; Ultra-performance liquid chromatographytandem mass spectrometry; Multi-pesticides residue;
- 【文献出处】 分析化学 ,Chinese Journal of Analytical Chemistry , 编辑部邮箱 ,2019年02期
- 【分类号】O657.63;X833
- 【被引频次】7
- 【下载频次】268