Issue 39, 2021

Application of new N- and S-doped amorphous carbon in D-μSPE and its combination with deep eutectic solvent-based DLLME for the extraction of some mycotoxins from soymilk

Abstract

A new amorphous carbon-based dispersive micro solid-phase extraction method was developed for the extraction and preconcentration of several mycotoxins from soymilk samples. The extracted analytes were concentrated by a deep eutectic solvent-based dispersive liquid–liquid microextraction method, and then, quantified by a high-performance liquid chromatography-fluorescence detector. The sorbent was prepared from β-cyclodextrin and methionine under mild conditions. The sorbent was doped by N and S, which improved its physicochemical properties. The optimization and validation of the method were performed using the “one-variable-at-a-time” method and International Council Harmonization guideline, respectively. Under the optimal conditions, low limits of detection and quantifications in the ranges of 0.08–0.56 and 0.27–1.9 ng L−1 were obtained, respectively. Also, intra- (n = 6) and inter-day (n = 6) precisions showed an acceptable repeatability of the present work as they were in the ranges of 3.9–6.2 and 4.6–8.9% at a concentration of 3 ng L−1 of each analyte, respectively. Finally, the proposed method was performed on different soymilk samples marketed in Tabriz city, and aflatoxin B1 was found in all samples. One soymilk was contaminated by ochratoxin A.

Graphical abstract: Application of new N- and S-doped amorphous carbon in D-μSPE and its combination with deep eutectic solvent-based DLLME for the extraction of some mycotoxins from soymilk

Supplementary files

Article information

Article type
Paper
Submitted
09 ذو القعدة 1442
Accepted
20 محرم 1443
First published
15 صفر 1443

Anal. Methods, 2021,13, 4604-4613

Application of new N- and S-doped amorphous carbon in D-μSPE and its combination with deep eutectic solvent-based DLLME for the extraction of some mycotoxins from soymilk

A. Rezaeefar, M. A. Farajzadeh, M. Nemati, M. R. Afshar Mogaddam and F. Lotfipour, Anal. Methods, 2021, 13, 4604 DOI: 10.1039/D1AY01057C

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