Mechanism of Smilax china L. in the treatment of intrauterine adhesions based on network pharmacology, molecular docking and experimental validation.

BACKGROUND: Smilax china L. (SCL) is a traditional herbal medicine for the potential treatment of intrauterine adhesion (IUA). However, the mechanisms of action have not yet been determined. In this study, we explored the effects and mechanisms of SCL in IUA by network pharmacology, molecular docking and molecular biology experiments. METHODS: Active ingredients and targets of SCL were acquired from TCMSP and SwissTargetPrediction. IUA-related targets were collected from the GeneCards, DisGeNET, OMIM and TTD databases. A protein‒protein interaction (PPI) network was constructed by Cytoscape 3.9.1 and analysed with CytoHubba and CytoNCA to identify the core targets. The DAVID tool was used for GO and KEGG enrichment analyses. Furthermore, molecular docking was employed to assess the interaction between the compounds and key targets. Finally, the mechanisms and targets of SCL in IUA were verified by cellular experiments and western blot. RESULTS: A total of 196 targets of SCL were identified, among which 93 were related to IUA. Topological and KEGG analyses results identified 15 core targets that were involved in multiple pathways, such as inflammation, apoptosis, and PI3K/AKT signalling pathways. Molecular docking results showed that the active compounds had good binding to the core targets. In vitro experiments showed that astilbin (AST), a major component of SCL, significantly reduced TGF-ß-induced overexpression of fibronectin (FN), activation of the PI3K/AKT signalling pathway and the expression of downstream factors (NF-κB and BCL2) in human endometrial stromal cells, suggesting that AST ameliorates IUA by mediating the PI3K/AKT/NF-κB and BCL2 proteins. CONCLUSIONS: AST, a major component of SCL, may be a potential therapeutic agent for IUA. Moreover, its mechanism is strongly associated with regulation of the PI3K/AKT signalling pathway and the downstream NF-κB and BCL2 proteins. This study will provide new strategies that utilize AST for the treatment of IUA.

Fully connected-convolutional (FC-CNN) neural network based on hyperspectral images for rapid identification of P. ginseng growth years.

P. ginseng is a precious traditional Chinese functional food, which is used for both medicinal and food purposes, and has various effects such as immunomodulation, anti-tumor and anti-oxidation. The growth year of P. ginseng has an important impact on its medicinal and economic values. Fast and nondestructive identification of the growth year of P. ginseng is crucial for its quality evaluation. In this paper, we propose a FC-CNN network that incorporates spectral and spatial features of hyperspectral images to characterize P. ginseng from different growth years. The importance ranking of the spectra was obtained using the random forest method for optimal band selection. Based on the hyperspectral reflectance data of P. ginseng after radiometric calibration and the images of the best five VNIR bands and five SWIR bands selected, the year-by-year identification of P. ginseng age and its identification experiments for food and medicinal purposes were conducted, and the FC-CNN network and its FCNN and CNN branch networks were tested and compared in terms of their effectiveness in the identification of P. ginseng growth years. It has been experimentally verified that the best year-by-year recognition was achieved by utilizing images from five visible and near-infrared important bands and all spectral curves, and the recognition accuracy of food and medicinal use reached 100%. The FC-CNN network is significantly better than its branching model in the effect of edible and medicinal identification. The results show that for P. ginseng growth year identification, VNIR images have much more useful information than SWIR images. Meanwhile, the FC-CNN network utilizing the spectral and spatial features of hyperspectral images is an effective method for the identification of P. ginseng growth year.

[Medicinal plant resources in Inner Mongolia autonomous region of China and Mongolia: a comparative study].

Inner Mongolia autonomous region of China and Mongolia are the primary regions where Chinese and Mongolian medicine and its medicinal plant resources are distributed. In this study, 133 families, 586 genera, and 1 497 species of medicinal plants in Inner Mongolia as well as 62 families, 261 genera, and 467 species of medicinal plants in Mongolia were collected through field investigation, specimen collection and identification, and literature research. And the species, geographic distribution, and influencing factors of the above medicinal plants were analyzed. The results revealed that there were more plant species utilized for medicinal reasons in Inner Mongolia than in Mongolia. Hotspots emerged in Hulunbuir, Chifeng, and Tongliao of Inner Mongolia, while there were several hotspots in Eastern province, Sukhbaatar province, Gobi Altai province, Bayankhongor province, Middle Gobi province, Kobdo province, South Gobi province, and Central province of Mongolia. The interplay of elevation and climate made a non-significant overall contribution to the diversity of plant types in Inner Mongolia and Mongolia. The contribution of each factor increased significantly when the vegetation types of Inner Mongolia and Mongolia were broadly divided into forest, grassland and desert. Thus, the distribution of medicinal plant resources and vegetation cover were jointly influenced by a variety of natural factors such as topography, climate and interactions between species, and these factors contributed to and constrained each other. This study provided reference for sustainable development and rational exploitation of medicinal plant resources in future.

Assessment of Carbon Sequestration Capacity of E. ulmoides in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6.

Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM-2·a-1. The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides.

The Impact of Traditional Chinese Medicine on Mitophagy in Disease Models.

Mitophagy plays an important role in maintaining mitochondrial quality and cell homeostasis through the degradation of damaged, aged, and dysfunctional mitochondria and misfolded proteins. Many human diseases, particularly neurodegenerative diseases, are related to disorders of mitochondrial phagocytosis. Exploring the regulatory mechanisms of mitophagy is of great significance for revealing the molecular mechanisms underlying the related diseases. Herein, we summarize the major mechanisms of mitophagy, the relationship of mitophagy with human diseases, and the role of traditional Chinese medicine (TCM) in mitophagy. These discussions enhance our knowledge of mitophagy and its potential therapeutic targets using TCM.

Evaluation of the Outcome of Antiviral Therapy among Individuals Infected HIV-1 in Suqian District of Jiangsu Province, China.

BACKGROUND: To evaluate the condition of antiviral therapy (ART) for individuals infected HIV-1 in Suqian district of Jiangsu Province, China. METHODS: Altogether, 561 HIV-positive patients who received antiviral therapy in Suqian district in 2019 were recruited. EDTA anticoagulated blood was collected and separated to obtain the plasma samples. Viral load (VL) were tested for evaluating the outcome of ART. Then samples with VL beyond 1000IU/mL were used to conduct the molecular test in order to master the characters of HIV-1 and the prevalence of resistance strains. RESULTS: VL results showed that the virus in 91.1% of the patients who received continuous antiviral treatment for more than 6 months were effectively inhibited (VL ≤ 1000 IU / ml). Among the 50 patients who failed in the treatment, 46 HIV-1 pol gene sequences were obtained, and the positive rate was 92.0%. The most prevalent strain was CRF_ 07bc (32.6%), and new epidemic strains, such as 67_01B, 79_0107, 87_cpx, were popular in this district. Drug resistance test results showed that 56.5% of the patients failed in antiviral treatment due to drug resistance, mainly resistant to the national first-line antiviral drug 3TC. Drug-resistant strains were not found in 43.5% of the patients. CONCLUSION: ART achieved a satisfied result in Suqian district, but the main cause resulting in ART-failure was resistant, so it is very necessary to enhance the education of adherence prior to the initiation of ART.

[Application of remote sensing technology in medicinal plant resources].

The sustainable use of medicinal plants is the foundation of the inheritance of traditional Chinese medicine(TCM) and the acquisition of information on medicinal plants is the basis for the development of TCM. The traditional methods of investigating medicinal plant resources are disadvantageous in strong subjectivity and poor timeliness, making it difficult to real-time monitor medicinal plant resources. In recent years, remote sensing technology has become an important means of obtaining information on medicinal plants. The application of this technology has made up for the shortcomings of traditional methods. The open-access remote sensing data with medium spatial resolution satellites provide an opportunity for extracting information on medicinal plant resources. This study firstly introduced the principles of remote sensing technology, summarized the satellites and the parameters commonly used in the field of medicinal plant resources, and compared the survey methods of remote sensing technology with traditional methods. Secondly, it reviewed the applications of remote sensing technology in the extraction of information on the cultivation of medicinal plants and the common methods for extracting the planting structure information of medicinal plants based on remote sensing technology. Thirdly, the applications of remote sensing technology in the investigation and monitoring of medicinal plants were further analyzed with the research objects divided into wild and cultivated medicinal plants according to the characteristics of the habitats. Finally, it pointed out the key unsolved technical problems in the remote sensing monitoring of medicinal plant resources, and proposed solutions for the intelligent information processing of medicinal plants based on remote sensing big data, which is expected to provide references for the development of remote sensing technology in derivative application in medicinal plant resources.

Jiuzhuan Huangjing Pills relieve mitochondrial dysfunction and attenuate high-fat diet-induced metabolic dysfunction-associated fatty liver disease.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common global chronic liver disease. Jiuzhuan Huangjing Pills (JHP) have been used for the treatment of human disease for over a thousand years, but their efficacy and underlying mechanism(s) of action against MAFLD are unknown. We investigated the alleviating effects of JHP on high-fat diet (HFD)-induced MAFLD. METHODS: In vitro and in vivo methods were used to evaluate the effects of JHP on MAFLD. L02 adipocyte models were induced by fat emulsion and adipocytes were treated with JHP for 24 h. MAFLD rat models were induced by HFD-feeding and were intragastrically administered JHP for 12 weeks. Changes in fat accumulation, L02 cell damage, body weight, food intake, histological parameters, organ indexes, biochemical parameters, and mitochondrial indicators including ultrastructure, oxidative stress, energy metabolism, and fatty acid metabolism were investigated. RESULTS: JHP attenuated the increase in levels of total cholesterol, triglyceride, low density lipoprotein cholesterol, alanine transaminase, and aspartate transaminase levels, and significantly increased high density lipoprotein cholesterol. JHP up-regulated levels of glutathione (GSH) and superoxide dismutase (SOD), and down-regulated malondialdehyde (MDA). JHP afforded protection to the mitochondrial ultrastructure, and inhibited the HFD-induced increase in MDA and the reduction of SOD, GSH, ATP synthase, and complex I and II, in liver mitochondria. JHP regulated the expression of ß-oxidation genes, including acyl-CoA dehydrogenase, cyl-CoA dehydrogenase long chain, carnitine palmitoyltransferase 1A, carnitine palmitoyltransferase 1B, peroxisomal proliferator-activated receptor-gamma coactivator-1α and peroxide proliferator activated receptor α. CONCLUSION: JHP alleviates HFD-induced MAFLD through the protection of mitochondrial function.

[Suitable planting area of Poria cocos in Jinzhai county of Dabie Mountains region].

Dabie Mountain in Anhui province is a genuine producing area of Poria cocos, commonly known as Anling. Jinzhai county in Anhui province is a traditional producing area of P. cocos, and it is also a key county for poverty alleviation in Dabie Mountains. Poverty alleviation of traditional Chinese medicine producing area is an important measure to implement the major strategic deployment of the central government. The planting of P. cocos is helpful to promote the development of traditional Chinese medicine industry in Dabie Mountains and help poverty alleviation. P. cocos is a saprophytic fungus with special demands on soil and ecological environment, and its planting appears a scattered and irregular distribution. Traditional investigation methods are time-consuming and laborious, and the results are greatly influenced by subjective factors. In order to obtain the suitable planting area of P. cocos in Jinzhai county, according to the field survey, the research team has explored the regional, biological characteristics and cultivation methods of P. cocos in the county, and obtained the altitude distribution area suitable for the growth of P. cocos. Then, the MaxEnt niche model was used to analyze the relationship between ecological factors and distribution areas, and the potential distribution zoning of P. cocos in Jinzhai county was studied. Combined with the characteristics of P. cocos planting pattern, taking ZY-3 remote sensing image as the data source, the maximum likelihood method was used to extract the area that could be used for P. cocos cultivation in Jinzhai county, and the reason why artificial planting P. cocos was mainly distributed in the west of Jinzhai county was analyzed. The suitable regional classification of P. cocos in Jinzhai county was obtained by superposition of suitable altitude distribution area, MaxEnt analysis and area extracted from remote sensing image, which provided data support for the planting planning of P. cocos in Jinzhai county.

[Contrastive analysis of extraction of Polygonatum cyrtonema planting area based on data of "Resource 3"].

Polygonatum cyrtonema is a famous bulk medicinal material which is the medicinal and edible homologous. With the implementation of the traditional Chinese medicine industry to promote precise poverty alleviation, the planting area of P. cyrtonema in Jinzhai is becoming larger and larger in recent years. Jinzhai is located in the Dabie Mountainous area, which is the largest mountain area and county in Anhui Province. The cultivation of P. cyrtonema is scattered, and the traditional Chinese medicine resources investigation is not only inefficient and accurate. In this study,the "Resource 3"(ZY-3) remote sensing image was used as the best observation phase,and the method of support vector machine classification was used. The method of parallelepiped, minimum distance, mahalanob is distance, maximum likelihood classification and neural net were used to classify and recognize the P. cyrtonema in the whole region. In order to determine the accuracy and reliability of classification results, the accuracy of six supervised classification results was evaluated by confusion matrix method, and the advantages and disadvantages of six supervised classification methods for extracting P. cyrtonema field planting area were compared and analyzed. The results showed that the method of support vector machine classification was more appropriate than that using other classification methods. It provides a scientific basis for monitoring the planting area of P. cyrtonemain field.

The Therapeutic Effect of Shugan Xiehuo Formula in the Female Rat Model with Central Precocious Puberty.

Central precocious puberty (CPP) severely affects children's physical and mental health and needs to be treated promptly and effectively. This article aimed to research the therapeutic effect of Shugan Xiehuo Formula (SXF) on CPP. A female CPP rat model was established and then treated with leuprolide and different doses of SXF. Sex organ volume and index were measured. Ovaries and uteri were visualized by hematoxylin-eosin staining. The concentrations of follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), and estradiol (E2) in peripheral blood were determined. The expression levels of gonadotropin-releasing hormone (GnRH), gonadotropin-releasing hormone receptor (GnRHR), estrogen receptor alpha (ERα), and G protein-coupled receptor 30 (GPR30) in the hypophysis were investigated by Real-Time Quantitative Reverse Transcription PCR and western blot. GnRH expression in the hypothalamus and GnRHR expression in the ovary were detected by immunohistochemistry. SXF reduced the volume of the bilateral ovaries, as well as the volumes of the uterus, hypothalamus, and hypophysis in the female CPP rats and diminished the index of the ovary, uterus, hypothalamus, and hypophysis in the female CPP rats (P < 0.05 or P < 0.01). SXF treatment inhibited follicle maturation and uterine wall thickening in the female CPP rats. SXF decreased the concentrations of FSH, LH, PRL, and E2 in the peripheral blood in the female CPP rats (P < 0.01 or P < 0.001). SXF suppressed the expressions of GnRH, GnRHR, ERα, and GPR30 in the hypophysis (P < 0.05), the expression of GnRH in the hypothalamus (P < 0.01), and the expression of GnRHR in the ovaries (P < 0.001) of the female CPP rats. Overall, our study revealed that SXF had therapeutic effects on CPP in female rats. This is worthy of promoting clinically.

Quality suitability regionalization analysis of Angelica sinensis in Gansu, China.

The genus Angelica encompasses 80 species worldwide. Among them, only Angelica sinensis is widely used in China and Japan. To explore the quality and geographical distribution of A. sinensis, we collected 1,530 plants from Gansu Province and analyzed them for their contents of chlorogenic acid (CA), ferulic acid (FA), senkyunolide I(SI), senkyunolide A(SA), senkyunolide H (SH), coniferyl ferulate (CF), ligustilide (LI), and butenyl phthalide (BP) using UPLC. We also assessed the relationship between the ecological environment and quality of A. sinensis through maximum entropy modeling and a geographical information system. The habitat suitability distribution demonstrated that the most influential ecological factors for the growth of A. sinensis were altitude, precipitation during March, May, and December, precipitation during the wettest month, and the soil pH. The most suitable areas for cultivation are concentrated to the south of Gansu Province, including Linxia Hui Autonomous Prefecture, Dingxi City, Tianshui City, south of Wuwei City, east of Gannan Tibetan Autonomous Prefecture, north of Longnan City, and northwest of Pingliang City. The quality suitability regionalization analysis divulged that the most influential ecological factors for the index components of A. sinensis were the altitude, sunshine, rainfall, temperature, and soil pH. The highest quality A. sinensis grow in Dingxi City, Tangchang, Lixian, and Wen counties in Longnan City, Wushan County in Tianshui City, Lintan, Zhouqu, and Zhuoni counties in Gannan Tibetan Autonomous Prefecture, Kangle and Linxia counties in Linxia Hui Autonomous Prefecture. The experiment yielded highly accurate results (accuracy of 0.955), suggesting that the results were consistent with the actual distribution of A. sinensis in Gansu. The inferences of this research will naturally draw the attention of the authorities in the fields of natural resources and agriculture departments and provide a scientific basis for the rational selection of A. sinensis cultivation areas.

Nonalcoholic Fatty Liver Disease: Pathogenesis and Treatment in Traditional Chinese Medicine and Western Medicine.

Nonalcoholic Fatty Liver Disease (NAFLD) is one of the most important causes of liver disease worldwide and probably destined to become the leading cause of end-stage liver disease in the coming decades, affecting both adults and children. Faced with the severe challenges for the prevention and control of NAFLD, this article discusses the understanding and mechanism of NAFLD from Chinese and Western medicine. Moreover, the progress regarding its treatment in both Chinese and Western medicine is also summarized. Both Chinese medicine and Western medicine have their own characteristics and clinical efficacy advantages in treating diseases. The purpose of this article is to hope that Chinese and Western medicine have complementary advantages, complementing each other to improve clinical NAFLD therapy prevention and treatment methods to receive more and more attention throughout the global medical community.

[Research on remote sensing recognition of wild planted Lonicera japonica based on deep convolutional neural network].

Identification of Chinese medicinal materials is a fundamental part and an important premise of the modern Chinese medicinal materials industry. As for the traditional Chinese medicinal materials that imitate wild cultivation, due to their scattered, irregular, and fine-grained planting characteristics, the fine classification using traditional classification methods is not accurate. Therefore, a deep convolution neural network model is used for imitating wild planting. Identification of Chinese herbal medicines. This study takes Lonicera japonica remote sensing recognition as an example, and proposes a method for fine classification of L. japonica based on a deep convolutional neural network model. The GoogLeNet network model is used to learn a large number of training samples to extract L. japonica characteristics from drone remote sensing images. Parameters, further optimize the network structure, and obtain a L. japonica recognition model. The research results show that the deep convolutional neural network based on GoogLeNet can effectively extract the L. japonica information that is relatively fragmented in the image, and realize the fine classification of L. japonica. After training and optimization, the overall classification accuracy of L. japonica can reach 97.5%, and total area accuracy is 94.6%, which can provide a reference for the application of deep convolutional neural network method in remote sensing classification of Chinese medicinal materials.

[Random forest classification of Callicarpa nudiflora from WorldView-3 imagery based on optimized feature space].

Taking the Xiushui township of Baisha county in Hainan province as the research area,the random forest algorithm with obvious advantages in feature selection and classification extraction was used to extract the information of the Callicarpa nudiflora planting in the study area. Firstly,four kinds of different characteristic variables were generated based on World View-3 data,including spectral features,principal component features,vegetation index and texture features. Secondly,the spatial distribution of the C. nudiflora in the study area was extracted by remote sensing by random forest classification algorithm. Finally,the feature space of the random forest classification algorithm was optimized based on the feature importance to obtain the best random forest classification results,and this result is compared with the classification result of the random forest algorithm of the unoptimized feature space. The results showed that:①The overall accuracy of the C. nudiflora extracted by World View-3 image was 89. 97%,and the Kappa coefficient was 0. 84,which indicates that the random forest algorithm had higher classification accuracy and better applicability in Hainan C. nudiflora recognition.② The overall accuracy of extracting C. nudiflora with the dimension reduction feature was 90. 4,and the Kappa coefficient was 0. 85,which indicates that the random forest algorithm can effectively select features. At the same time as the feature variable data mining,the precision of the information extraction of the C. nudiflora was still guaranteed,and the operation efficiency was improved. This study provides a new idea,method and technical means for information extraction of cultivated medicinal plant resources in terms of feature selection and method selection.

[Application of UAV remote sensing in monitoring of Callicarpa nudiflora].

In order to solve the problem of manual area measurement,the traditional methods of medicinal planting area statistics are difficult to meet the needs of rapid area survey application. This paper uses the UAV remote sensing method with the advantages of unmanned,automatic,high efficiency,high score and short production cycle to monitor the shape of Callicarpa nudiflora. A solution for aerial photography,image data acquisition and data processing of drones were designed for characteristics and planting conditions. After data processing and statistical analysis,detailed information on the location and area of the C. nudiflora in the target area was obtained. Then the accuracy comparison analysis was carried out with the measured results of the C. nudiflora. The results show that the UAV is feasible for the monitoring of C. nudiflora,and has a good application prospect in the monitoring of Chinese herbal medicine planting.

[Regional cultitvation and dynamic change of garden Ginseng in Changbai county based on multi-source and multi-temporal satellite remote sensing data].

The dried roots of Panax ginseng are used as medicines. In this paper,multi-time satellite sensing image data are used for image registration by radiometric correction,atmospheric pressure correction,the data of different years were compared. The multiscale segmentation of the sensing image was successively carried out by using object-oriented method. Combining with the characteristics of the sensing image participated in the field survey,the objective was to understand the speckles of the environmental parameters distribution map of Changbai county in 2017 and 2018. The parameter area of Changbai county was calculated by using GIS spatial analysis tools. The union,erase and intersect tools of " analysis to OLS" overlay in " Arc Toolbox" were used to analyze the parametric area of Changbai county from 2017 to 2018. The results showed that the parameter area of Changbai county in 2017 was 27 400 mu( 1 mu≈667 m2),and the parameter area in 2018 was 13 900 mu. The parameter area of the new park in Changbai County in 2018 was 12 500 mu,and the harvested area in 2017 was 27 000 mu. Through the analysis and study of the regional change of the park participating in the training area,it has significance for guiding the park participating in the actual production planning and layout in Changbai county in the next step.

[Study of extracting natural resources of Chinese medicinal materials planted area in Luoning of Henan province based on UAV of low altitude remote sensing technology and remote sensing image of satellite].

The study is aimed to effectively obtain the planting area of traditional Chinese medicine resources. The herbs used as the material for traditional Chinese medicine are mostly planted in natural environment suitable mountainous areas. The UAV low altitude remote sensing data were used as the samples and the GF-2 remote sensing images were applied for the data source to extract the planting area of Salvia miltiorrhiza and Artemisia argyi in Luoning county combined with field investigation. Remote sensing satellite data of standard processing obtain specific remote sensing data coverage. The UAV data were pre-processed to visually interpret the species and distribution of traditional Chinese medicine resources in the sample quadrat. Support vector machine( SVM) was used to classify and estimate the area of traditional Chinese medicine resources in Luoning county,confusion matrix was used to determine the accuracy of spatial distribution of traditional Chinese medicine resources. The result showed that the application of UAV of low altitude remote sensing technology and remote sensing image of satellite in the extraction of S. miltiorrhiza and other varieties planting area was feasible,it also provides a scientific reference for poverty alleviation policies of the traditional Chinese medicine Industry in local areas.Meanwhile,research on remote sensing classification of Chinese medicinal materials based on multi-source and multi-phase high-resolution remote sensing images is actively carried out to explore more effective methods for information extraction of Chinese medicinal materials.

[Extracting Paeonia lactiflora planted area in Dangshan of Anhui province based on ZY-3 remote sensing image].

In order to comprehensively monitor the dynamic change of Paeonia lactiflora planting area,the investigation of P. lactiflora planting area in Dangshan was carried out. It can provide reference for the planting detection of P. lactiflora in Huaibei Plain.Based on remote sensing technology,this paper extracts the planting area of P. lactiflora in Dangshan in 2018 by using the minimum distance method,maximum likelihood method,parallel hexahedron method and Mahalanobis distance method,using the remote sensing image of ZY-3 Satellite as the data source,and makes a comparative analysis with the results. The results show that the maximum likelihood method is better than the other three methods. This method can provide reference for remote sensing monitoring of P. lactiflora planting area in China.

[Planting area estimation of Paeonia ostii based on RS--by case study in Dangshan of Anhui province].

Moutan Cortex is one kind of famous medicinal materials. The dry root bark of Paeonia ostii which is a genuine medicinal material produced in Tongling,Anhui province,and later was introduced to Heze,Shandong province and Bozhou,Anhui province.Dangshan county is located at the northern end of Anhui province and adjacent to Shandong province. Its medicinal seedlings were came from Heze,Shandong province. At present,there is a lack of scientific investigation on the planting area of P. ostii in north China plain. On the basis of field investigation and remote sensing technology,through the data source provided by the remote sensing image of " Resources 3"( ZY-3),combined with the biological characteristics of P. ostii,the planting area of P. ostii in Dangshan county was extracted by field investigation and supervisory classification. The supervise classification method with the highest interpretation accuracy so far,the overall accuracy was 97. 81%,Kappa coefficient 0. 96. The results showed that the remote sensing classification method based on the maximum likelihood classification could extract P. ostii plots in the study area effectively. This study provides a scientific basis for the protection and rational utilization of traditional Chinese medicine resources,the development policy of traditional Chinese medicine industry and the long-term development plan in Dangshan county,and provides technical support for the poverty alleviation of traditional Chinese medicine industry in Dangshan county. It provides scientific reference for the application of remote sensing technology to investigate the planting area of P. ostii in in north China plain.