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基于化学计量学设计的绿色、选择性和廉价的可切换亲水性溶剂液相微萃取程序优化,用于牛奶、蜂蜜和水样中磺胺嘧啶的预浓缩和萃取。

Chemometric design-based optimization of a green, selective and inexpensive switchable hydrophilicity solvent-based liquid phase microextraction procedure for pre-concentration and extraction of sulfadiazine in milk, honey and water samples.

机构信息

Sivas Cumhuriyet University, Faculty of Science, Department of Chemistry, Sivas, Turkey.

出版信息

Food Chem. 2022 Nov 15;394:133540. doi: 10.1016/j.foodchem.2022.133540. Epub 2022 Jun 21.

DOI:10.1016/j.foodchem.2022.133540
PMID:35763903
Abstract

In this research, a green, selective and inexpensive switchable hydrophilicity solvent-based liquid phase microextraction (SHS-LPME) procedure has been optimized for the extraction and preconcentration of sulfadiazine (SDZ) in milk, honey and water samples prior to spectrophotometric analysis. Five variables affecting the SHS-LPME procedure were optimized using chemometric-based central composite design. For the SHS-LPME procedure, analytical parameters such as linearity, limit of detection, extraction recovery and enrichment factor were 15-300 μg L, 4.5 μg L, 96 ± 3% and 113, respectively. The precision of the method was investigated by repeatability and reproducibility studies. The relative standard deviation from these studies was found in the range of 2.4-4.5%. The recovery of the SDZ in the samples was in the range of 94 ± 4-99 ± 2%. Collected samples were analyzed by both the SHS-LPME procedure and the reference method using flow injection-flame atomic absorption technique, and the results were compared. There was no statistically significant difference between the two methods. This showed that the SHS-LPME procedure can be safely applied to the analysis of real samples.

摘要

在这项研究中,优化了一种基于绿色、选择性和廉价的可切换亲水性溶剂液相微萃取(SHS-LPME)程序,用于在分光光度分析之前萃取和预浓缩牛奶、蜂蜜和水样中的磺胺嘧啶(SDZ)。使用基于化学计量的中心复合设计优化了影响 SHS-LPME 程序的五个变量。对于 SHS-LPME 程序,分析参数如线性、检测限、萃取回收率和富集因子分别为 15-300μg L、4.5μg L、96±3%和 113。通过重复性和重现性研究研究了该方法的精密度。这些研究的相对标准偏差在 2.4-4.5%范围内。SDZ 在样品中的回收率在 94±4-99±2%范围内。使用流动注射-火焰原子吸收技术,通过 SHS-LPME 程序和参考方法对收集的样品进行了分析,并对结果进行了比较。两种方法之间没有统计学上的显著差异。这表明 SHS-LPME 程序可以安全地应用于实际样品的分析。

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