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A new GIS model for ecologically suitable distributions of medicinal plants

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BackgroundThe endangered rate of medicinal plant exceeds that of endangered plant species. However, blindly introducing medicinal plants in regions without comprehensively considering the involved environmental factors results in diseases and… Click to show full abstract

BackgroundThe endangered rate of medicinal plant exceeds that of endangered plant species. However, blindly introducing medicinal plants in regions without comprehensively considering the involved environmental factors results in diseases and insect pests and the consequent overproof pesticide residue as well as reduces the quality of herbal medicine produced.MethodsGlobal Medicinal Plant Geographic Information System (GMPGIS) was developed to analyze environmental information of ecologically suitable regions, thus guiding the conservation and introduction of medicinal plants. This system is based on theories and methods from multiple disciplines, including computer science, geoinformatics, ecology, and traditional herbal medicine. Using a range-based method, the previously established ecologically suitable regions were evaluated. This new method effectively resolved the problem of outlier points, and its functions were implemented in Python. The system automatically calculates the Euclidean distance of climatic factors and intersection of soil factors, thus identifying regions with high ecological similarity and those are climatically and edaphically suitable for the cultivation of medicinal plants.ResultsThese results, validated using real-world regions, revealed that GMPGIS is highly accurate in screening ecologically suitable regions for the cultivation of medicinal plants worldwide.ConclusionsOverall, because of these features, the GMPGIS is considered as a suitable distribution analysis system for global medicinal plant cultivation.

Keywords: medicine; ecologically suitable; system; medicinal plants; medicinal plant

Journal Title: Chinese Medicine
Year Published: 2019

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