| The application of traditional Chinese medicine(TCM) and their preparations have a long history. Varieties, producing area, collecting, processing and preparation techniques are the important factors that influences the quality of TCM. Establish a scientific medicine quality evaluation method is to ensure that clinical drug safety,effectiveness and stability of the premise. With the deepening of the research, market demand is increasing, wild resources are limited to the needs of the market. Rational use of non-medicinal parts and medicine standardized cultivation have been given greater attention. Multiple cropping systems is a way to relieve the shortage of TCM resources and enhance the utilization ratio of land. The cultivation of TCM improving the biodiversity of environment, protecting the ecological environment, the unity of economic benefit.Gentiana rigescens Franch. is a perennial herb, which belongs to family of Gentianaceae. Have the activities of eliminating damp-heat, quenching the fire of the liver and gall bladder. As one of the clinical commonly used TCM. Fourier transform infrared spectroscopy(FTIR) is a feasible, rapid and non-destructive method to study of TCM.It can be used to quantify the amount of a particular compound in a mixture.Using Fourier transform infrared spectroscopy combined with chemometrics methods to study wild and cultivated, different parts, harvest time, different planting patterns,different processed of G. rigescens samples. The result indicated are as following:1). The various parts of wild and cultivated G. rigescens were high similar the peaks at 1732, 1643, 1613, 1510, 1417, 1366, 1322, 1070 cm-1 were the characteristic peak of esters, terpenoids and saccharides, respectively. The shape and peak intensity were more distinct in the second derivative spectrum of samples.2). Remove noise spectrum, the spectra range was from 1800 to 600 cm-1, the method standard normal variate(SNV) combined with second derivative(SD) and Savitaky-Golay(SG) smoothing present the best result of spectra pretreatment. The contribution rates of first three principal components were 92.47 % with principal component analysis(PCA). Small differences were found for the samples harvested in May, September and October. Same spectrum range was chosen and partial least square discriminant analysis(PLS-DA) was applied to establish the model. The R2 and RMSEE were 0.9678, 0.0860, respectively, and the prediction accuracy is 100 %.3). The differences of effective components in the samples with different planting patterns were represented by the variances of spectral matching values. The difference of matching values of samples planted with Juglans regia, Alnus nepalensis,Eucalyptus robusta and Alnus nepalensis were lower than that with slope and Chaenomeles sinensis. The number of misjudgment of expert retrieval, correlation retrieve and square differential retrieve were 11, 4 and 9, respectively. The discrimination result of correlation retrieve was the best in the full spectral range and the correct recognition rate was 94.29 %.4). The accumulation contribution rate of first three principal components is94.05 %. Most of the information to reflect the original data. There were differences among different samples. The result of discriminant analysis showed that the recognition rate of G. rigescens samples could achieve to 100 % based on baseline correction and normalization treatment combined with multiple scattering correction(MSC) and the precondition of principal component scores for 10. |
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