食品工业科技2018，Vol.39Issue(8)：199-204,209,7.DOI:10.13386/j.issn1002-0306.2018.08.036
QuEChERS结合GC-MS法快速检测酿酒玉米中14种邻苯二甲酸酯类塑化剂
Rapid determination of 14 phthalate esters in corn by QuEChERS-based gas chromatography/mass spectrometry method
摘要
Abstract
A modified QuEChERS method was developed for the simultaneous determinationn of 14 phthalate esters (PAEs)in corn prior to gas chromatography-mass spectrometry (GC-MS) analysis.All of the PAEs in corn samples were extracted into acetonitrile and salted out by anhydrous MgSO4 and NaCl.Then,the PAEs in the supernatant after clean-up by primary secondary amine(PSA),octadecyl silica (C18),and graphitized carbon black (GCB) were subjected to GC-MS analysis.External standard quantification was used to determine the extraction efficiency of each sample.As a result,14 PAEs possessed an excellent linear relation by using matrix-matched curve under 1～500 μg/L,and the correlation coefficients were 0.9945～0.9995.The recoveries of 14 PAEs in corn matrixes at three spiked levels of 15,150 and 500μg/kg ranged from 80.0％ to 109.8％ with relative standard deviations below 9.0％.The LODs and LOQs for PAEs,based on S/N of 3 and 10,ranged from 0.1 to 2.5 μg/kg and 0.13 to 5.0 μg/kg,respectively.The applicability of the method was properly validated using six corns,and the results revealed that the dimethyl phthalate (DMP),diethyl phthalate (DEP),diisobutyl phthalate (DIBP),dibutyl phthalate (DBP),and bis (2-methoxyethyl) phthalate (DEHP) were detected in all the samples.The content of PAEs is lower than the standard of GB.Overall,the developed QuEChERS-GC/MS method could be considered as a promising method for routine monitoring of PAEs residue in corn since the procedure was easy,fast,and effective.关键词
QuEChERS/玉米/邻苯二甲酸酯类塑化剂/气相色谱-质谱法Key words
QuEChERS/corn/phthalate esters (PAEs)/gas chromatography-mass spectrometry (GC-MS)分类
轻工纺织引用本文复制引用
孙啸涛,刘淼,曾凤鸣,敖灵,孙宝国,孙金沅,郑福平,黄明泉,李贺贺..QuEChERS结合GC-MS法快速检测酿酒玉米中14种邻苯二甲酸酯类塑化剂[J].食品工业科技,2018,39(8):199-204,209,7.基金项目
国家自然科学基金青年科学基金项目(31601556) （31601556）
“十三五”国家重点研发计划重点专项(2016YFD0400501) （2016YFD0400501）
四川省科技计划项目(2017JZ0012). （2017JZ0012）
