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| Study on Rapid Detection Method of Danofloxacin Mesylate and Ofloxacin Residues in a Chicken Based on Synchronous Fluorescence Spectrum |
| CHEN Jian1, HUANG Jun-shi1, 2, LIU Mu-hua1, 2, YUAN Hai-chao1, 2, HUANG Shuang-gen1, 2, ZHAO Jin-hui1, 2*, XU Ning1, WANG Ting1, HU Wei1 |
1. Jiangxi Provincial Key Laboratory of Modern Agricultural Equipment, Jiangxi Agricultural University, Nanchang 330045, China
2. Jiangxi Provincial Collaborative Innovation Center of Key Technologies and Quality and Safety in Post-Harvest Processing of Fruits and Vegetables, Jiangxi Agricultural University, Nanchang 330045, China |
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Abstract The rapid detection for danofloxacin mesylate (DFM) and ofloxacin (OFL) residues in chicken were achieved through synchronous fluorescence technology coupled with chemometric methods. First of all, the synchronous fluorescence spectra of DFM standard solution, OFL standard solution, chicken extract without antibiotics and chicken extract containing DFM and OFL were analyzed, and the wavelength difference (Δλ) of DFM and OFL were respectively determined as 130 and 200 nm, and the fluorescence excitation peaks of DFM and OFL were respectively determined as 288 and 325 nm for the detection of DFM and OFL in chicken, respectively. Subsequently, the effects of the concentrations of sodium hydroxide solution and the type of surfactant on the fluorescence intensities were investigated through the single factor test. The best detection conditions of DFM and OFL residues in chicken were as follows: the concentration of sodium hydroxide solution of 0.1 mol·L-1, and the concentration of SDS solution of 0.1 mol·L-1. Finally, the prediction models of DFM and OFL residues in chicken were established using linear regression, partial least squares regression (PLSR), and multiple linear regression (MLR), respectively. The experimental results showed that the comprehensive evaluation of DFM residues’ prediction model of based on the PLSR algorithm was best among these algorithms. The coefficient of determination for the prediction set (R2P) and the root mean square error for the prediction set (RMSEP) were 0.978 3 and 1.934 2 mg·kg-1. The ratio of prediction to deviation (RPD) was 5.876 5. The comprehensive evaluation of the prediction model of OFL residues based on the MLR algorithm was best among these algorithms. The R2P, RMSEP, and RPD were 0.895 0, 3.859 8 mg·kg-1, and 2.509 1, respectively. The adopted method was simple and fast, and could to realize the rapid detection of DFM and OFL residues in chicken.
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Received: 2020-04-21
Accepted: 2020-07-16
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Corresponding Authors:
ZHAO Jin-hui
E-mail: 9115328@qq.com
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