Study On Fingerprints Technique For Quality Control Of Some Chinese Traditional Medicines And Foodstuffs

Fingerprints are the standardized maps, which are gained by modern instruments and multiple analysis methods, to reflect characteristics of the traditional Chinese medicine(TCM) or food. Fingerpints have the features of systematic, holistic and stability, and could be seen as integrated means to apply in quality control of traditional Chinese medicine and food.In the introduction, first, introduce the development of TCM and food. TCM play an important part in our country, it has great contribution to the prevention and treatment of diseases for thousands of years. Food is the most basic necessities of human survival, in the three elements of food-safety, nutrition, appetite, safety is the primary criterion for consumers to take considered when they choose food, for food security directly effect on people's health and life and it has become the focus of attention. Then, describes the significance of quality control in TCM and food. Besides, introduce some commonly analysis technologies for construct fingerprints and the popular chemometrics methods used in fingerprints.First, near-infrared spectroscopy combined with chemometrics to recognition of toothpaste of different brands. There are many kinds of toothpaste with different brands, and the toothpaste with different kinds and brands generally show different properties and functions. In this research, take advantage of near-infrared spectroscopy, combined with some pattern recognition methods to fast determinate the brands of toothpaste and evaluate the immanent quality of toothpaste.Then, Chromatographic profiles of Rhizoma et Radix Notoperygii (RRN,"Qianghuo" in Chinese), were collected by high-performance liquid chromatography with a diode array detection (HPLC-DAD) at330nm. These data profiles were used as fingerprints to investigate quality control/classification modeling of the RRN samples. In this paper, all chromatographic profile data were pre-processed by the correlation optimized warping (COW) method and polynomial functions; then, these data were submitted as fingerprints (variables) for classification on the basis of sample origins. Chemometrics methods used for calibration modeling and subsequent sample classification-least square support vector machine (LS-SVM), artificial neural network (ANN) and partial least square discriminant analysis (PLS-DA), all produced satisfactory calibrations as well as classification results.Near-infrared (NIR) spectroscopy combined with chemometric was investigated to discriminate the wild and cultivated A. auricula. In order to eliminate uninformation variables and get better discrimination accuracy, three methods including independent component analysis (ICA), genetic algorithm (GA) and Successive projections algorithm (SPA) were used to extracted features wavelengths (FWs) after the original spectra preprocessed by Savitzky-Golay smoothing (SG) and standard normal variate (SNV). The preprocessed spectra data and FWs as input variables to principal component analysis (PCA), comparison of the scores on the first two PCs. After that, LS-SVM, KNN and PLS-DA models were developed to distinguish the wild and cultivated A. auricula. Comparison of prediction results, show that ICA-LS-SVM and GA-KNN is the optimal models to discriminate wild and cultivated A. auricular.In the end, high performance liquid chromatography combined with gas chromatograpy to identification of Bupleurum chinense DC and Bupleuruin scorzoneri folium Wild. Establish of two dimension fingerprinting of62radix bupleuri samples. Principal component analysis of one dimension fingerprints and two dimension ones, besides, call for the three supervise pattern recognition methods, which are LS-SVM, LDA and KNN, to compare the prediction result of one dimension data and two dimension data, and the result show that the two dimension fingerprints give a better identification of different species radix bupleuri samples.In my research, the fingerprints constructed by different analysis method could distinction and identification of four different brands of toothpaste, Qianghuo from different origins, wild and cultivated A. auricular, as well as Bupleurum chinense DC and Bupleuruin scorzoneri folium Wild combined with chemometrics. In the study that discriminate the origins of Qianghuo, take advantage of all chromatography profile instead of common peaks as input variables, and outcome research shows it could more effective to identify the origins. Besides, the research on distinction of the Bupleurum chinense DC and Bupleuruin scorzoneri folium Wild(chaihu). Used both HPLC and GC to get the comprehensive fingerprints of chaihu, and gain a better result than one-dimensional chromatography.However, in all reasearches, the problem that the components in study objects weren't identified is the main disadvantadge, and I will try my best to solve this problem in future jobs.