Suppr超能文献

Determination of trace levels of triazines in corn matrices by bar adsorptive microextraction with a molecularly imprinted polymer.

作者信息

Andrade Felipe Nascimento, Ide Alessandra Honjo, Neng Nuno da Rosa, Lanças Fernando Mauro, Nogueira José Manuel Florêncio

机构信息

Institute of Chemistry of Sao Carlos, University of Sao Paulo, Sao Carlos, SP, Brazil.

Centro de Química e Bioquímica, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Lisboa, Portugal.

出版信息

J Sep Sci. 2016 Feb;39(4):756-61. doi: 10.1002/jssc.201501101.

Abstract

This manuscript addresses the determination of triazines (ametryn, atrazine, simazine, and terbutryn) in corn matrices using bar adsorptive microextraction coated with a selective molecularly imprinted polymer phase following microliquid desorption and high-performance liquid chromatography with diode array detection. The molecularly imprinted polymer was synthesized using atrazine as a template and methacrylic acid as a functional monomer. Assays performed in 25 mL of ultrapure water samples spiked at 8.0 μg/L yielded 80-120 % recoveries under the evaluated experimental conditions. The method showed an accuracy (0.2 < bias < 17.9%), precision (relative standard deviation <17.4%), convenient detection (0.2 μg/L), and quantification (0.7 μg/L) limits, as well as linear dynamic ranges (0.8-24.0 μg/L) with remarkable determination coefficients (R(2) > 0.9926). The proposed analytical method was applied to monitor triazines in three types of corn matrices using the standard addition methodology. Experiments performed in corn samples spiked with triazines at the trace level (8.0 μg/kg of each analyte) gave rise to recoveries (81.0-119.4%) with good reproducibility and robustness. The proposed methodology is also easy to implement and showed to be a good analytical alternative to monitor triazines in complex matrices, when compared with other sorption-based microextraction techniques.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验