[Rapid determination of ractopamine content in pork by using three-dimensional synchronous fluorescence spectrum coupled with APTLD].

In order to realize the rapid determination of ractopamine content in pork, quantitative determination model of ractopamine content in pork was established by using three-dimensional synchronous fluorescence spectrum coupled with alternating penalty trilinear decomposition (APTLD). Firstly, the generation mechanism of the fluorescence spectrum for ractopamine and three-dimensional synchronous fluorescence spectrum for samples were analyzed. Secondly, concentration quenching phenomenon of fluorescence of ractopamine in pork extract was investigated. Thirdly, the number of components for three linear decomposition of APTLD was set as 2 by using the core consistency diagnostic method, and the calibration curve of the relative fluorescence intensity of ractopamine between pork extract and the training sample was established for the correction of relative fluorescence intensity of prediction samples. Finally, three-dimensional synchronous fluorescence spectrum combined with APTLD was used to build the prediction model of ractopamine content in pork. The experimental results showed that the method adopted in the paper could better solve the problem of serious synchronous fluorescence spectrum overlapping between ractopamine in pork samples and backgrounds, and leave out some trivial process of chemical separation for the identification of ractopamine in pork. The determination coefficient (R2) and the root mean squared error of prediction (RMSEP) for the model proposed in this paper were 0.986 3 and 0.496 6 mg x L(-1), respectively. The method in this paper has achieved the goal of rapid quantitative detection of ractopamine content in pork.

[Rapid determination of tetracycline content in duck meat using particle swarm optimization algorithm and synchronous fluorescence spectrum].

Tetracycline under the condition of NaOH could be degraded to iso tetracycline which has strong fluorescent characteristic, and the prediction model of tetracycline contents in duck meat was developed with the combination of synchronous fluorescence 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 wavelengths 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 using 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 x 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.

[Study on determination of carbaryl content in duck meat based on synchronous fluorescence spectroscopy].

For the rapid detection of carbaryl residue in duck meat, synchronous fluorescence spectroscopy was used, and GA combined with SVR was used to establish regression forecasting mode for the application of forecasting carbaryl residue in duck meat. Firstly, fluorescence spectrophotometer was used to get the 3D synchronous fluorescence spectra of carbaryl hydrolysate and duck solution containing carbaryl, and 140 nm was selected as the optimum wavelength difference delta lambda; Secondly, some concentration quenching was analysed. Finally, GA was used to optimize and choose the 3D synchronous fluorescence spectra. According to the root mean square error of cross-validation (RMSECV) 21 characteristic wavelengths were chosen, then the full wavelength and 21 characteristic wavelengths were used as input characteristic variables of SVR regression forecasting model respectively. At last the results showed that characteristic wavelengths chosen by GA can get better forecasting results, and the correlation coefficient of the prediction samples set and the root mean squared error (RMSEP) were 0.976 4 and 12.232 2, respectively. The results of experiments showed that the synchronous fluorescence spectroscopy could be used to detect carbaryl residue in duck meat efficiently and rapidly when combined with GA-SVR.