采用三维荧光光谱法实现对蜂蜜中的3种喹诺酮类抗生素(氟甲喹、恩诺沙星和左氧氟沙星)残留样本的数据测量,对所得光谱消除了二级瑞利散射和拉曼散射的干扰,采用小波优化集合经验模态分解(EEMD)的方法消除光谱噪声,完成了预处理过程。采用双线性最小二乘/残差双线性(BLLS/RBL)算法分别对预处理前后的样本进行定性、定量检测。结果表明:经预处理后可以准确地解析出样本中各组分光谱,且与原光谱有着极高的相似度。定量分析中,氟甲喹、恩诺沙星和左氧氟沙星的预测平均加标回收率RA分别为94.99%,100.20%,103.20%;均方根误差RMSE分别为4.03,0.21,0.29μg/L;灵敏度SL分别为3.2×103,3.5×104,3.3×104μg/L;检测下限Lout分别为2.08,0.18,0.19μg/L;优于未经预处理的结果。
Abstract
Three kinds of quinolones (fluoroquinoline, enrofloxacin and levofloxacin) in honey were analyzed by three-dimensional fluorescence spectroscopy. The spectra were pretreated to eliminate the second-order Rayleigh scattering and Raman scattering, and the spectral noise was eliminated by wavelet optimization set ensemble empirical mode decomposition (EEMD). The bilinear least square/residual bilinear (BLLS/RBL) algorithm was used to detect the samples before and after pretreatment. The results show that after pretreatment, the spectrum of each component in the sample can be accurately resolved, and it has a high similarity with the original spectrum. In the quantitative analysis, the predicted average recovery (RA) of fluoroquinoline, enrofloxacin and levofloxacin is 94.99%, 100.20%, 103.20% respectively, the root mean square error (RMSE) is 4.03, 0.21, 0.29μg/L respectively, the sensitivity (SL) is 3.2×103, 3.5×104, 3.3×104μg/L, respectively; and the detection lower limit (Lout) is 2.08, 0.18, 0.19μg/L respectively, which are superior to the results without pretreatment.
关键词
计量学;抗生素残留检测;双线性最小二乘/残差双线性;小波优化;集合经验模态分解 /
喹诺酮类抗生素;蜂蜜质量
Key words
metrology /
antibiotic residue testing /
BLLS/RBL /
wavelet optimization /
EEMD /
quinolones /
honey quality
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基金
国家自然科学基金(61771419);河北省自然科学基金(F2017203220); 中央引导地方科技发展资金(206Z0401G)
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