Suitability Evaluation And Genome Size Determination Of Medicinal Plant Resources Of Scutellaria Baicalensis

Scutellaria baicalensis Georgi (Scutellaria, Labiatae), a perennial herb, is one ofthe commonly used traditional Chinese medicine. Its air-dried root has pharmacological effects of clearing heat and detoxication, anti-inflammation, choleretic, anti-oxidation and inhibiting HIV-RT viruses. Currently,70%of Chinese patent medicines for clearing heat and detoxication or their prescriptions contain the active ingredients of S. baicalensis. The growing demand for S.baicalensis has led to the excavation of wild resources as well as the sharp decrease of species distribution. It is thus becoming serious regarding the contradiction between growing market demand and exhausted wild resources. Although the cultivation area of S. baicalensis is increasing, the plantation was mainly based on subjective experience of local farmers. Furthermore, it lacks appropriate suitability evaluation and plantation regionalization, which will bring certain blindness and risks exist for practical clutivation. Predicting the suitable habitat of S. baicalensis and the environmental variables determining its potential distribution and medicinal quality will provide valuable references for the plantation and standardized cultivation of S. baicalensis.In this study, we conducted potential distribution prediction and suitability evaluation, as well as the environmental variables determining the distribution and medicinal quality of S. baicalensisusing GIS based Maxent modelingand Fuzzy logics and other five Scutellaria plantsusing GIS based Maxent modeling. Meanwhile, we optimized the FCM estimation methods of genome size of S. baicalensis and first estimated the genome size of66medicinal plants. The main results were as below:1. Based on the previous collection of198occurrence records and275baicalin data, we conducted potential distribution prediction and suitability evaluation of S. baicalensis using GIS and combined Maxent and Fuzzy logics. The results of16environmental variables in Maxent modeling exhibited a very good simulation accuracy (AUC=0.952±0.006). The variables of alt, prec7, precl, bio4, biol and t_pH were determined as the six key environmental variables affecting the distribution and baicalin content of S. baicalensis. The potential distribution region of S. baicalensis was located in the northeast, the north and the northwest of China. The most suitable region was located in the southeast of Inner Mongolia, Hebei and Shanxi provinces, and the regions in the north Qinling in Shaanxi province, where Shanxi (112285km2), Inner Mongolia (92342km2), Shaanxi (75441km2) and Hebei (72878km2) provinces cover the largest areas. The above prediction results will provide theoretical references for the conservation and restoration and plantation regionalization of S. baicalensis.2. We used combined GIS and Maxent modeling to conduct potential distribution prediction and suitability evaluation of S. scordifolia, S. viscidula, S. rehderiana, S. amoena and S. likiangensis, respectively. The results of Maxent modeling showed a very good accuracy. The north of Inner Mongolia, Hebei, Shanxi and Shaanxi were determined as the main distribution region of S. scordifolia and S. viscidula, while the distribution of S. rehderiana, S. amoena and S. likiangensis exhibited regional trend. Further analysis indicated that the key environmental variables of six medicinal plants are not consistent, suggesting that different environmental variables were the main reason that leading to the differences of systematics, potential distribution and phenotypic traits of the six medicinal plants. This result will provide valuable references for the conservation, domestication and plantation of Scutellaria plants, and lay foundation for revealing the geographical origins and systematics of Scutellaria plants.3. Based on the above results of potential distribution and suitability evaluation, we conduct primary plantation regionalization of S. baicalensis in Shaanxi province combing with the geographical, climactic and topographical maps. The most suitable regions of S. baicalensis consists of three sub regions. The first region is Yan’an-Great Wall Region and North Weinan-Yan’an Loess Plateau Region located in the North warm temperate zone. The second region includes Heyang-Chengcheng Region and the central Shaanxi-Weihe Plain Region. The third region is Qin-Ba Mountain Hilly Region located in South Shaanxi. These results will provide scientific references for the utilization and conservation of medicinal plant resources as well as land use capability in Shaanxi Province.4. We used fresh, young and silica gel-dried leaves of S. baicalensis as materials, and Otto and LB01as extraction buffers to explore and optimize the estimation methods of genome size for medicinal plants using flow cytometry (FCM). The results showed that the optimal condition is determined as that using Pisum sativum as internal standard and fresh and young leaves as materials, and using Otto’s buffer with two-steps method to extract, prepare and store under low temperature with the concentration of propidium iodide (PI) at0.02mg/mL. The estimation results according to above procedure showed better results were easily and accurately gotten with relatively concentrated scatterplot, less debris, more simplicity to take gates and lower coefficient of variance (CV). As a result, the C-value of S. baicalensis was first estimated successfully as1C=0.58pg, and the genome size was562Mbp by FCM. According to this method, we then estimated the DNA C-value of80commonly used Chinese medicines in Shaanxi province, and66of these data of genome size were first reported. Consequently, these estimations were submitted to the Plant DNA C-values Database (http://data.kew.org/cvalues/). Our results here will lay foundation for the genetic evaluation, systematics and evolution of functional traits of medicinal plants.