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Issue 31, 2018
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A novel fluorescence sensing method based on quantum dot-graphene and a molecular imprinting technique for the detection of tyramine in rice wine

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Abstract

Tyramine, an important biogenic amine, occurs in high amounts in certain processed food products and can cause adverse health effects in people. In this study, we developed a simple method to produce a molecularly imprinted fluorescence sensor with high sensitivity and selectivity for tyramine. The reverse microemulsion method was applied to prepare a carrier material, hydrophobic CdSe/ZnS quantum dots (QDs) sensitized with carboxylated graphene (Gra), which was added to the reaction for synthesizing molecularly imprinted polymers (MIPs) using 3-mercaptopropyltriethoxysilane (MPTES) as the functional monomer and tetraethylorthosilicate (TEOS) as the crosslinking agent in the presence of tyramine as the target molecule. The novel sensing material, Gra-QDs@MIPs, was selective for tyramine and generated a concentration-dependent fluorescence signal. Under optimized conditions, the limit of detection was 0.021 mg L−1 and the linear range of detection was 0.07–12 mg L−1. Importantly, we tested the performance of the Gra-QDs@MIPs with real-world samples by demonstrating that they selectively detected around 0.08 or 2 mg L−1 of tyramine in spiked rice wine samples. Hence, the described molecularly imprinted fluorescence sensor for tyramine could serve as a prototype for developing MIP-based assays for food analysis.

Graphical abstract: A novel fluorescence sensing method based on quantum dot-graphene and a molecular imprinting technique for the detection of tyramine in rice wine

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Publication details

The article was received on 18 May 2018, accepted on 12 Jun 2018 and first published on 17 Jul 2018


Article type: Paper
DOI: 10.1039/C8AY01117F
Anal. Methods, 2018,10, 3884-3889

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    A novel fluorescence sensing method based on quantum dot-graphene and a molecular imprinting technique for the detection of tyramine in rice wine

    Q. Wang and D. Zhang, Anal. Methods, 2018, 10, 3884
    DOI: 10.1039/C8AY01117F

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