Optimization of the determination of deoxynivalenol in corn samples by liquid chromatography and a comparison of two clean-up principles

Author:

Abramovic Biljana1ORCID,Jajic Igor2,Juric Verica2,Gaál Ferenc1

Affiliation:

1. Faculty of Science - Department of Chemistry, Novi Sad

2. Faculty of Agriculture, Department of Animal Science, Novi Sad

Abstract

The determination of deoxynivalenol (DON) in corn by liquid chromatography with DAD detection was optimized. The separations were achieved on a Hypersil ODS column (100 x 4.6 mm; particle size 5 ?m) by isocratic elution (0.6 cm3/min), a mobile phase consisting of acetonitrile?water in the ratio of 16:84. UV Detection was performed at 220 nm. Linear calibration curves were constructed in the concentration range of 0.72 ? 12.00 ng/?l (equivalent to 0.29 ? 4.8 ?g/g com). The detection limit measured as the signal-to-noise ratio (3:1) was 0.16 ng/?l for DON (equivalent to 0.06 ?g/g corn). The efficiencies of two clean-up principles for crude corn extract were compared solid-phase and immunochemical extraction. The efficiency of solid-phase extraction was found to be higher, with a value of 92.7 % when MycoSep 225 columns were used, while its value was 97.6 % when self-made activated charcoal?alumina?Celite?cationic columns were used. In contrast, the efficiency of the immunochemical columns (IMA) was only 73.8%. It was also found that the self-made columns could be used at least three times in a row in that way differing from the MycoSep 225 columns, which could not be reused either with or without regeneration, as well as from the IMA columns, which had a regeneration efficiency of 53.6 %.

Publisher

National Library of Serbia

Subject

General Chemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3