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Detection of Inosine Monophosphate (IMP) in Meat Using Double-Enzyme Sensor

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Inosine monophosphate (IMP) was considered to be an important component of meat flavor and an important indicator for evaluating the quality of meat products. This paper developed a novel dual-enzyme… Click to show full abstract

Inosine monophosphate (IMP) was considered to be an important component of meat flavor and an important indicator for evaluating the quality of meat products. This paper developed a novel dual-enzyme biosensor for the quantitative detection of inosinic acid to assess meat quality. Using the conductivity of MXene materials and the ability of Au@Pt nanoflowers to catalyze the oxidation of H 2 O 2 , a dual-enzyme biosensor was assembled and prepared for sensitive and rapid detection of IMP. The MXene-Ti 3 C 2 Tx material had 2D nanostructure similar to that of graphene, as well as metal conductivity and good biocompatibility. MXene was used as a carrier for 5′-nucleotidase and xanthine oxidase, with good biological environment and stable microenvironment. Bimetallic nanoflowers with a core-shell structure had better ability to catalyze H 2 O 2 than the single metal. The double-enzyme hydrolyzed IMP to produce the H 2 O 2 . The Au@Pt nanoflowers of the sensor can catalyze the decomposition of H 2 O 2 , which causes electron transfer to produce current change. Therefore, the content of IMP is indirectly obtained by monitoring the current change. The results showed that the linear range of the double-enzyme biosensor was 0.04~17 g L −1 , the correlation coefficient was 0.9964, and the detection limit was 2.73 ng mL −1 . The biosensor had great reproducibility and stability. Compared with high-performance liquid chromatography, biosensors could quickly and accurately detect the content of inosine monophosphate in meat, and provided a better method to detect the quality index of meat products.

Keywords: imp; detection; double enzyme; enzyme; meat; inosine monophosphate

Journal Title: Food Analytical Methods
Year Published: 2019

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