SERS结合PCA-LDA分析鉴别鸡肉中硝基呋喃类代谢物的混合残留

以纳米Au溶胶和NaCl溶液为活性增强基底,对鸡肉中残留的两种呋喃它酮代谢物(AMOZ)和呋喃妥因代谢物(AHD)进行表面增强拉曼光谱(SERS)快速检测技术研究。采用自适应迭代惩罚最小二乘法消除原始数据中的背景干扰,应用标准归一化进行光谱预处理,并结合主成分—线性判别方法(PCA-LDA)建立识别模型,得出模型校正集的判别正确率为90.48%,预测集的判别正确率为94.29%。研究表明,SERS技术与PCA-LDA相结合可以有效地鉴别出鸡肉样本中残留的AMOZ和AHD。

Identification of nitrofuran metabolites in chicken by using surface-enhanced Raman spectroscopy coupling with principal component analysis-linear discriminant analysis

Surface-enhanced Raman spectroscopy (SERS) using gold (Au) nanoparticles and NaCl solution as SERS enhanced substrate was applied to rapidly identify furaltadone metabolite (AMOZ) and nitrofurantoin metabolite (AHD) residues in chicken samples. The background interference was eliminated by using adaptive iterative re-weighted penalized least squares (air-PLS), and the spectra data was preprocessed by standard normalization. The samples of four groups, i.e. chicken extract containing AHD, AMOZ, AHD and AMOZ, and control, were marked in sequence, and the identification model was established by combining the principal component analysis and linear discriminant analysis (PCA-LDA). The experimental results showed that the correct discriminant rate of the calibration set was 90.48%, and the correct discriminant rate of the prediction set was 94.29%. Consequently, AHD and AMOZ residues in chicken samples could be identified effectively by using SERS and PCA-LDA.