Quality Assessment Of Some Complex Substances By Fingerprint Techniques With The Aid Of Chemometrics

This study is concerned with the research and development of methodology for the quality analysis of the common medicine food homology materials, with the aid of chemometrics and high end instruments, not only a fuzzy and efficient fingerprint is constructed for each material, but also the active contents who give the huge explained variance for discrimination are qualified and deteriminated; this study focus on the study to admire the multi-way fingerprints advantage compared with single-way fingerprints, and to valid the role on which the active compoents play in the fingerprints discrimination. This study is detailed described as:1. Face the fact that the fingerprints constructed by two data sets (L and R) of Shaoyao samples which were measured by high performance liquid chromatography (HPLC) and Fourier transform infrared spectroscopy (FT-IR), does not obtain satisfactory results. So two statistical methods for fusing the two data set were developed based on:(i) four PCs from the L and R matrices, and (ii) selection of optimum variables by the genetic algorithm-partial least squares (GA-PLS). Moreover, pattern recognition methods were used to assess the fingerprint, non-linear Radial basis function artificial neural network (RBF-ANN) and Least squares-support vector machine (LS-SVM) models obtanined good results.2:As described in study1, only HPLC data gave insufficient information for discriminating Shaoyao samoles, so multi-wavelength combined HPLC methods were researched and developed in order to compare their performance for the classification of complex substances. Three different supervsed pattern recognition methods were used; the results showed that, irrespective of the chemometrics method used, the multi-wavelength data produced better classification results, in additional, LS-SVM models were significantly better in classifying the herb samples.3:In order to identify whether the compoents of origin Yujin medicine, water exacts, and essential oils do exist differerce in different species and different batchs or not, so three different fingerprints, consisting of HPLC, GC-MS, and Ultraviolet-Visible-Near infrared spectroscopy fingerprints, were constructed to test it. Via the analysis KKAnalysis and LS-SVM, we get the conclusions that UV-Vis-NIRs fingerprints show Yujin from different batches and different species really has differences; GC-MS fingerprints indicate the biggest difference for Yujin samples came from the different species; while the LC fingerprints state that samples between "guang2011" and "guang2010" really have great differences.4:In order to evaluate the relation between the contents of markers compounds and different origins of Yimucao (HL). So in this work, HPLC and chemical methods were applied to separate and determine the marker alkaloids and flavonoids, such as rutin, apigenin, quercetin, kaempferol, leonurine, and total alkaloids. However, the results appeared that just a few types of compound are not sufficient to indicate fully the performance of a given HL sample with respect to its medicinal effect. Consequently, the analytical data was submitted to multi-variate data analysis so as to probe deeper into the information embedded in the HPLC fingerprints, principal component analysis (PCA) obtained good results with consequent discrimination of the HL samples according to their geographical origins; Interestingly, it was found that the highly correlated L6(kaempferol) and L7(apigenin) loadings were independent with the other five marker compound loadings (L1-L5).