Detection of Enrofloxacin residues in chicken based on surface enhanced Raman spectroscopy and two-dimensional correlation spectroscopy
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    Abstract:

    The surface-enhanced Raman spectroscopy (SERS) technology and the two-dimensional correlation spectroscopy (2D-COS) were used to optimize the characteristic variables of the Enrofloxacin in chicken meat. The partial least squares regression method (PLSR) was used to establish Enro the characteristic peak analysis model of sand star was compared with the competitive positive adaptive weighting algorithm (CARS). The results showed that the 2D-COS-PLSR model has the best effect, and its Rc and Rp were 0.979 7, 0.997 2 respectively, which shows that it is feasible to use 2D-COS to optimize the characteristic spectral peaks related to the concentration of enrofloxacin in chicken.

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班晶晶,刘贵珊,何建国,等.基于表面增强拉曼光谱与二维相关光谱法检测鸡肉中恩诺沙星残留[J].食品与机械英文版,2020,(7):55-58.

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  • Online: February 17,2023
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