应用粒子群优化算法对鸭肉中四环素残留含量的同步荧光光谱快速测定  

Rapid Determination of Tetracycline Content in Duck Meat Using Particle Swarm Optimization Algorithm and Synchronous Fluorescence Spectrum

作　　者：赵进辉[1] 袁海超[1] 刘木华[1] 肖海斌[1] 洪茜[1] 徐将[1] 

机构地区：[1]江西农业大学工学院,生物光电及应用重点实验室,江西南昌330045

出　　处：《光谱学与光谱分析》2013年第11期3050-3054,共5页Spectroscopy and Spectral Analysis

基　　金：国家科技支撑计划课题(2012BAK17B02);国家自然科学基金项目(31101295);国家高技术研究发展技术(863计划)项目(2008AA10Z209);江西省科技厅对外科技合作计划项目(20132BDH80005);江西省科技厅科技支撑项目(20121BBG70058);江西省教育厅科技计划项目(GJJ12244)资助

摘　　要：四环素在NaOH存在的条件下能降解生成具有强荧光特性的异四环素,应用同步荧光光谱结合小波去噪、粒子群优化算法(PSO)和支持向量回归(SVR)建立鸭肉中四环素残留含量的预测模型,可实现鸭肉中四环素残留含量的快速测定和提高预测模型的精度。首先应用平行因子分析法(PARAFAC)确定检测鸭肉中四环素含量的最佳波长差Δλ为70nm;然后对同步荧光光谱进行db6小波的2层分解的小波去噪及去噪后的光谱归一化处理,并利用PSO筛选出了6个荧光特征波长;最后应用PSO优化SVR模型参数(c,g),进而对在PSO筛选的特征波长光谱条件下建立的PSO-SVR,PLS,PCR模型以及在全光谱条件下建立的PSO-SVR模型进行性能比较,结果表明,以在PSO筛选的特征波长光谱条件下建立的PSO-SVR模型预测能力更强,其预测集的相关系数(r)和均方根误差(RMSEP)分别为0.952 0和17.6mg·kg-1。说明PSO能够有效提取鸭肉中残留四环素所对应的荧光特征波长,且PSO-SVR预测模型能满足鸭肉中残留四环素的快速测定要求。Tetracycline under the condition of NaOH could be degraded to iso tetracycline which has strong fluorescent character istic, and the prediction model of tetracycline contents in duck meat was developed with the combination of synchronous fluores cence spectrum, wavelet de-noising, particle swarm optimization algorithm （PSO） and support vector regression （SVR）, and it could realize the rapid prediction of tetracycline contents in duck meat and improve the accuracy of prediction model. In the process, 70 nm was selected as the optimum wavelength difference for the determination of tetracycline contents in duck meat by using parallel factor analysis （PARAFAC）. Secondly, the db6 wavelet with 2 levels decomposition was used to reduce the noise of synchronous fluorescence spectrum, and the spectrum after wavelet de-noising was normalized, and 6 characteristic wave lengths were selected by using PSO. Lastly, the SVR model parameters （c, g） were optimized by using PSO. Furthermore, the performances of the models of PSO-SVR, PLS and PCR under the spectral condition of characteristic wavelengths selected by u- sing PSO, and PSO-SVR under the spectral condition of full spectrum were compared. The experimental results showed that the predictive ability of the model of PSO-SVR under the spectral condition of characteristic wavelengths selected by using PSO was strongest, and the correlation coefficient and the root mean squared error of prediction were 0. 952 0 and 17. 6 mg . kg-1 , respectively. This work proved that PSO could extract effectively the characteristic wavelengths of tetracycline in duck meat, and the model of PSO-SVR could satisfy the request of rapid determination of tetracycline contents in duck meat.

关 键 词：同步荧光光谱 粒子群优化算法 支持向量回归 小波去噪 四环素 鸭肉 

分 类 号：O657.31[理学—分析化学]