Abstract
A visual fluorescence quenching immunoaffinity test column (FQ-ITC) assay was developed for the simultaneous detection of malachite green (MG) and crystal violet (CV) residues in aquatic products. The proposed FQ-ITC assay was based on fluorescence resonance energy transfer from the fluorescence donor (quantum dot) to the fluorescence acceptor (MG or CV) and the specific identification between the analytes and their polyclonal antibodies. The process can be completed within 10 min, and the results can be observed by the naked eye. After the evaluation of the specificity and sample matrix effect, the established FQ-ITC was found to be successfully applied in the detection of MG or CV in grass carp, striped bass, carp, and shrimp, with a visual limit of detection of 2 μg/kg. The accuracy of the FQ-ITC assay was verified by comparison with liquid chromatography-tandem mass spectrometry. The simple, time-saving, sensitive, and visual observation characteristics make the established FQ-ITC assay an effective analytical tool for the simultaneous detection of MG and CV in aquatic products.
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Funding
This work was supported by grants from the Ministry of Science and Technology of the People’s Republic of China (Project No. 2016YFD0400401), Tianjin Municipal Science and Technology Commission (Project No. 16PTSYJC00130), and the International Science and Technology Cooperation Program of China (Project No. 2014DFR30350).
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Yiyuan Chen declares that he has no conflict of interest. Minling Ding declares that she has no conflict of interest. Jiaqi Li declares that she has no conflict of interest. Wei Sheng declares that she has no conflict of interest. Bing Liu declares that she has no conflict of interest. Yan Zhang declares that she has no conflict of interest. Shuo Wang declares that he has no conflict of interest.
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Chen, Y., Ding, M., Li, J. et al. Fluorescence Quenching Immunoaffinity Test Column with Quantum Dots as Fluorescence Donors for the Quick Detection of Malachite Green and Crystal Violet in Aquatic Products. Food Anal. Methods 11, 3362–3370 (2018). https://doi.org/10.1007/s12161-018-1312-0
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DOI: https://doi.org/10.1007/s12161-018-1312-0