ABSTRACT
Quality variation and ecotype classification of Chinese herbal medicine are important scientific problems in Daodi herbal medicine research. The diversity of natural environmental conditions has led to form unique multi-Daodi, multi-product areas that produce particular Chinese herbal medicine. China is one of three big American ginseng (Panax quinquefolium L.) producing areas worldwide, with over 300 years of application and 40 years of cultivation history. Long-term production practice has led to the formation of three big advocate produce areas in China: Northeast province, Beijing and Shandong. P. quinquefolium L. grown under certain environmental conditions will develop long-term adaptations that will lead to more stable strains (different ecotypes). P. quinquefolium L., can vary greatly in quality; however, the ecological mechanisms causing this variation are still unclear. Root samples were collected from four-year-old cultivated P. quinquefolium L. plants in the three major genuine (Daodi) American ginseng-producing areas of Northeast province, Beijing and Shandong province, China. Ultra-performance liquid chromatography was used to analyze the contents of eight ginsenosides (Rg1, Re, Rb1, Rb2, Rb3, Rc, Rd, Rg2). Data for nine ecological factors, including temperature, moisture and sunlight, were obtained from the ecological database of Geographic Information System for Traditional Chinese Medicine. Soil samples from the sampling sites were collected. Effective boron and iron, available nitrogen and potassium, as well as other trace elements and soil nutrients, were determined by conventional soil physicochemical property assay methods. Analytical methods of biostatistics and numerical taxonomy were used to divide ecotypes of the three main Panax quinquefolium L. producing areas in China based on ginsenoside content, climate, soil and other ecological factors. To our knowledge, this is the first time that ecological division of P. quinquefolium L. producing areas in China has ever been conducted. The results show that there are two chemoecotypes of P. quinquefolium L. in China: ginsenoside Rb1-Re from outside Shanhaiguan, and ginsenoside Rg2-Rd from inside Shanhaiguan. Similarly, there are two types of climatic characteristics: inside Shanhaiguan (Beijing, Shandong) and outside Shanhaiguan (Northeast). This suggests that the formation and differentiation of chemoecotypes of P. quinquefolium L. is closely related to variability of the climatic and geographical environment. Additionally, ecological variation of the three main producing areas, characteristics of two climatic ecotypes, and soil characteristics are also discussed and summarized. These results provide experimental scientific evidence of the quality variation and ecological adaptation of P. quinquefolium L. from different producing areas. They also deepen our understanding of the biological nature of Daodi P. quinquefolium L. formation, and offer novel research models for other multi-origin, multi-Daodi Chinese herbal medicines ecotypes. In addition, the results demonstrate the critical need for improving quality, appropriate ecological regionalization and promoting industrialized development of P. quinquefolium L.
ABSTRACT
The quality of Chinese herbal medicine is closely related to its producing region. In order to apply mathematical models to do a quantitative study on the suitability of Chinese herbal medicine, it is necessary to study on the ecological factors and the interpolation of climatic data, which influence the Chinese herbal medicine growth. The paper firstly studied the judgment standard of ecological index from the points of ecology and statistics, and how to calculate the optimum range values and the weight of each ecological factor. Secondly, meteorological element data is essential data in analyzing the suitable region of Chinese herbal medicine, and the spatial distribution of meteorological elements is closely related to terrain environment, so, in order to make the results close to true value by the greatest degree. The paper adopted multiple linear regression interpolation method which based on DEM. The paper distinguished the factor system of suitable region and interpolation on the point of datumization, and made a study on it about some key issues.