Study On The Application Of Infrared Spectroscopy And Chemometrics For Disease Diagnosis And Determination Of The Contentsof Target Compounds In Licorice

In this dissertation,we mainly study the qualitative and quantitative models based on Fourier Transform Infrared Spectroscopy(FTIR-ATR)and near-infrared spectroscopy(FTIR-NIR)for rapid screening of neonatal phenylketonuriaand simultaneous determination of glycyrrhizin and glycyrrhizic acid in licorice.Fourier Transform Infrared Spectroscopy-Attenuated Total Refraction(FTIR-ATR)were researched to rapidly screen the phenylketonuria(PKU)and the determination of glycyrrhizic acid and glycyrrhizic acid in licorice by near infrared reflectance spectroscopy.To develop the quantitative calibration model of the content of target components,the methods of partial least squares(PLS),consensus partial least squares(cPLS),kernel partial least squares(KPLS)and consensus kernel partial least squares(cKPLS),which the spectra data were preprocessed before,such as smoothing,derivative,principal component analysis,uninformative variables elimination,normalization.and the performance of the model was evaluated with various evaluation indexes.In this research,a methodology reference of application on the infrared spectra(IR)screening disease and the simultaneous determination of the composition of TCM was provided.Research 1: Using FTIR / ATR spectroscopy to establish different calibration models,and applied to neonatal phenylketonuria screening.The concentrations of Phe and Tyr of 69 dried blood samples were determined by tandem mass spectrometry,and the spectra of samples were collected by FTIR / ATR.partial least squares(PLS),kernel partial least squares(KPLS),consensus partial least squares(cPLS)and consensus kernel partial least squares(cKPLS)were to construct the calibration model of Phe concentration coupled with the spectra sample preprocessing by means of smoothing,derivative,vector normalization.The model was evaluated by determining the determination coefficient(R2),root mean square error(RMSE),mean relative error(MRE)and so on.The results show that the cKPLS model has the best performance and the result is more accurate and stable,which provides a basis for the establishment of robust FTIR / ATR spectrum model and other complicated calibration of FTIR / ATR spectra,which successfully applied to predict Phe concentrations in neonates with phenylketonuria.Research 2:Using infrared spectroscopy combined with PCA or clustering analysis for the identification of licorice origin.After pretreatment of the original spectrum,the principal component analysis and clustering analysis were performed by SPSS or MATLAB program respectively.Compared with the clustering results of the two methods,it was found that SPSS clustering was better than MATLAB program.It can be found that when inter-class distance of SPSSis 5.0,40 experimental samples can be divided into four categories: Class I for all Inner Mongolia samples;? class 5 of Gansu samples,8 samples of Inner Mongolia,2 Xinjiang,1 Ningxia together;? class,including 1 Gansu,1 Xinjiang,1 Inner Mongolia;? class,including 10 of Gansu samples,6 samples of Inner Mongolia,2 Xinjiang,1 Ningxia together as a class;and when the inter-class distance of MATLAB is 50,40 experimental samples were divided into eight categories,and there is no focus on a cluster of origin.Research 3: To establish a method for simultaneous determination of glycyrrhizin and glycyrrhizic acid by Near Infrared Spectroscopy and Partial Least Squares in Licorice.The contents of glycyrrhizin and glycyrrhizic acid in HPLC was used as the reference value to correlate the near-infrared spectroscopy(NIRS),which were to establish the quantitative analysis model of glycyrrhizin and glycyrrhizic Acid in licorice by PCA combined with PLS.The optimal model of glycyrrhizin wasthe determination coefficients of the training set,the determination coefficients of the validation set,the corrected mean square error(RMSEC)and the validation mean square error(RMSEP)were 0.9522,0.9305,0.0004 and 0.0017,respectively.The optimal model of glycyrrhizic acid was,the determination coefficients of the training set,the determination coefficients of the validation set,the corrected mean square error(RMSEC)and the validation mean square error(RMSEP)were were 0.9766,0.9591,0.0006 and 0.0021,respectively.The results showed that the quantitative analysis model established by near-infrared spectroscopy was able to quickly and non-destructively determine the content of glycyrrhizin and glycyrrhizic acid.