High-throughput determination of fungicides in grapes using thin-film microextraction coupled with liquid chromatography-tandem mass spectrometry
文献类型： 外文期刊
作者： Zhang, Zong-hui 1 ; Zhao, Hui-yu 3 ; Shen, Qian 1 ; Qi, Pei-pei 3 ; Wang, Xin-quan 3 ; Xu, Hao 3 ; Di, Shan-shan 3 ; Wang 1 ;
作者机构： 1.Nanjing Tech Univ, Jiangsu Natl Synerget Innovat Ctr Adv Mat, Key Lab Flexible Elect, Nanjing 211816, Peoples R China
2.Nanjing Tech Univ, Jiangsu Natl Synerget Innovat Ctr Adv Mat, Inst Adv Mat, Nanjing 211816, Peoples R China
3.Zhejiang Acad Agr Sci, Inst Qual & Stand Agr Prod, Hangzhou 310021, Peoples R China
关键词： fungicides; grape; high-throughput analysis; thin-film microextraction
期刊名称：JOURNAL OF SEPARATION SCIENCE （ 影响因子：3.645； 五年影响因子：2.943 ）
ISSN： 1615-9306
年卷期： 2020 年 43 卷 8 期
页码：
收录情况： SCI
摘要： A high-throughput and environmentally friendly method based on 96-well plate thin-film microextraction was established to determine 14 fungicides in grapes and grape juice using liquid chromatography-tandem mass spectrometry. The thin-film microextraction optimized method consisted of 60 min of extraction at pH 6.0 with the addition of sodium chloride (2-5%). Acetonitrile/water in the ratio of 8:2 was used for desorption analytes for 60 min. Evaluation of different extractive phases showed that polyacrylonitrile-polystyrene-divinylbenzene was the optimum coating. The linearity of the method was good in the range of 0.01-0.5 mu g/mL for 14 fungicides with determination coefficients (R-2) from 0.990 to 0.999, which indicated good linearity for both the grape juice and grape matrixes. The limit of detection was in the range of 0.002-0.01 mu g/mL. The limit of quantitation was in the range of 0.01 mg/kg according to the minimum fortified level. The average absolute recoveries of the 14 fungicides ranged from 75.0 to 118.3%. The intraday relative standard deviation (n = 4) and interday relative standard deviation (n = 4) were 5.6-13.0% and 1.6-6.4%, respectively. This study showed that this method can be used for analyzing 96 samples in parallel, and the sample preparation time was approximately 2.0 min per sample. In addition, this approach offers a green and low-cost sample pretreatment technique for future analyses.
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