Journal
FOOD ANALYTICAL METHODS
Volume 13, Issue 2, Pages 420-432Publisher
SPRINGER
DOI: 10.1007/s12161-019-01652-y
Keywords
Transition metal carbide; Au@Pt nanoflowers; Enzyme biosensor; Inosine monophosphate
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Funding
- National Natural Science Foundation of China [31772068, 31701681, 31872909]
- Special Project of Independent Innovation of Shandong Province [2018CXGC0214]
- Shandong Provincial Natural Science Foundation [ZR2017BC001, ZR2018ZC0126, ZR2018BC055]
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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 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 H2O2, 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 H2O2 than the single metal. The double-enzyme hydrolyzed IMP to produce the H2O2. The Au@Pt nanoflowers of the sensor can catalyze the decomposition of H2O2, 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 similar to 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.
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