Résumé
Objective:To explore the potential suitable distribution area and the high-quality distribution area of <italic>Sabia parviflora</italic>. Method:Combined with the distribution information and environmental factors，the maximum entropy （MaxEnt） model and ArcGIS software were used to predict the potential suitable distribution area of <italic>S. parviflora</italic>. Based on the correlation between environmental factors and total saponins，total flavonoids，quercetin-3-<italic>O</italic>-gentiobioside，camellianoside，tsubakioside A，kaempferol-3-<italic>O</italic>-rutinoside and isobariclisin-3-<italic>O</italic>-rutinoside，the quality regionalization was conducted by using spatial interpolation method and fuzzy superposition function in ArcGIS software. Result:<italic>S. parviflora</italic> is mainly distributed in Yunnan，Guizhou，Guangxi province in China. The medium and high suitable areas accounts for about 2.88% of the national area. The precipitation in October and November，the precipitation in the warmest and driest seasons，the standard deviation of seasonal changes in temperature and altitude are the main environmental factors that affect the distribution of <italic>S. parviflora</italic>. Slope，precipitation，solar radiation and temperature change had great influence on the accumulation of secondary metabolites. Based on the results of potential suitable distribution and spatial interpolation of each component，the high-quality areas of <italic>S. parviflora</italic> are mainly concentrated in the southwest of Guizhou，with Qinglong，Guanling，Zhenning，Pu'an，Xingren county and other areas as the core. Conclusion:This study provides a scientific guidance for the site selection of artificial planting and the procurement of medicinal materials for <italic>S. parviflora</italic>.
Résumé
This research was performed to establish the HPLC fingerprint of Sabia parviflora. HPLC method was carried out on a Thermo Accucore-C18(4. 6 mm×150 mm,2. 6 μm) column by 30% tetrahydrofuran in methyl alcohol-acetonitrile-0. 1% phosphate solution as mobile phase at a flow rate of 1. 0 m L·min-1,the column temperature was 30 ℃ and the detection wavelength was 360 nm. The fingerprints were further evaluated by chemometrics methods including similarity analysis,hierarchical clustering analysis,and principal component analysis. In HPLC fingerprint,15 common peaks were selected as the common peaks,and 6 contents of them were identified. The similarity degrees of 38 batches of the samples was more than 0. 710,and the samples were divided into 6 clusters by their quality difference. The method was precision,repeatable,stable,simple and reliable,which could be used for quality control and evaluation of S. parviflora.