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A Cu/β-cyclodextrin/reduced graphene oxide nanocomposite for efficient and multi-aflatoxin detection in rice, ginger and bean samples.

作者信息

Shahryari Behnaz, Khani Rouhollah, Feizy Javad

机构信息

Department of Chemistry, Faculity of Science, University of Birjand, Birjand 97179-414, Iran.

Department of Food Safety and Quality Control, Research Institute of Food Science and Technology (RIFST), Mashhad, Iran.

出版信息

Anal Methods. 2025 Jan 2;17(2):339-348. doi: 10.1039/d4ay01846j.

Abstract

Aflatoxins (AFs) are some of the most important mycotoxins or fungal toxins that cause contamination of food products and are considered a threat to human and animal health. An efficient Cu/β-cyclodextrin/reduced graphene oxide nanocomposite (Cu/β-CD/rGO) has been prepared and applied as a new solid-phase extraction adsorbent for the separation and preconcentration of four AFs (B, B, G, and G) using high-performance liquid chromatography with fluorescence detection (HPLC-FLD). The successful synthesis of the prepared nanocomposite was confirmed using Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM). The impacts of pH, amount of adsorbent, sample volume, desorption solvent volume, and salt concentration on the recovery of AFs were precisely investigated and optimized by central composite design (CCD). Under the optimal conditions, the introduced method demonstrated good linearity in the range of 0.4-5.4, 0.08-1.08, 0.4-5.4, and 0.08-1.08 ng g for AFs B, B, G and G, respectively. The limits of detection and quantification for the four AFs were obtained in the range of 0.06-0.53 and 0.20-1.62 ng g, respectively. The accuracy of the method was evaluated using recovery measurements in spiked real samples such as rice, bean, and ginger samples, and satisfactory recoveries were obtained in the range of 83.5-109.0% with good precision (RSDs between 2.4 and 8.6%). The results of this research revealed that our developed method is sensitive, highly effective, and convenient to perform for the trace analysis of AFs in different real samples.

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