Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing
To provide high-quality Astragalus mongholicus Bunge to domestic and foreign markets and maintain sustainable development of the A. mongholicus industry, Firstly, we evaluated the impact of environmental factors and planting areas on the A. mongholicus industry. The maximum entropy method (MaxEnt) w...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2022.908114/full |
| _version_ | 1811325513013133312 |
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| author | Ru Zhang Ru Zhang Mingxu Zhang Yumei Yan Yuan Chen Linlin Jiang Xinxin Wei Xiaobo Zhang Huanting Li Minhui Li Minhui Li Minhui Li Minhui Li Minhui Li |
| author_facet | Ru Zhang Ru Zhang Mingxu Zhang Yumei Yan Yuan Chen Linlin Jiang Xinxin Wei Xiaobo Zhang Huanting Li Minhui Li Minhui Li Minhui Li Minhui Li Minhui Li |
| author_sort | Ru Zhang |
| collection | DOAJ |
| description | To provide high-quality Astragalus mongholicus Bunge to domestic and foreign markets and maintain sustainable development of the A. mongholicus industry, Firstly, we evaluated the impact of environmental factors and planting areas on the A. mongholicus industry. The maximum entropy method (MaxEnt) was utilized to simulate the suitability distribution of A. mongholicus and establish the relationship between the active component contents of A. mongholicus and ecological factors through linear regression analysis. The random forest algorithm was subsequently used to perform feature selection and classification extraction on Sentinel-2 imagery covering the study area. Furthermore, the planting, processing, and sales of A. mongholicus in Guyang County were investigated, and the roles of stakeholders in the value chains were analyzed. The results demonstrated that precipitation of the warmest quarter, minimum temperature of the coldest month, standard deviation of seasonal temperature changes, range of mean annual temperature, and mean diurnal range [mean of monthly (max temp - min temp)] were the five environmental variables that contributed the most to the growth of A. mongholicus. The most influential factor on the distribution of high-quality A. mongholicus was the mean temperature of the coldest quarter. The classification results of image features showed that the planting areas of A. mongholicus was consistent with the suitable planting areas predicted by MaxEnt, which can provide data support to the relevant departments for the macro development of the A. mongholicus industry. In the production of A. mongholicus, 10 value chains were constructed, and the study demonstrated that the behavior of stakeholders, target markets, and the selected planting area had a significant impact on the quality of A. mongholicus. |
| first_indexed | 2024-04-13T14:34:32Z |
| format | Article |
| id | doaj.art-09efdbe64f28494ca84f455b3e40471f |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-04-13T14:34:32Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-09efdbe64f28494ca84f455b3e40471f2022-12-22T02:43:05ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2022-07-011310.3389/fpls.2022.908114908114Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote SensingRu Zhang0Ru Zhang1Mingxu Zhang2Yumei Yan3Yuan Chen4Linlin Jiang5Xinxin Wei6Xiaobo Zhang7Huanting Li8Minhui Li9Minhui Li10Minhui Li11Minhui Li12Minhui Li13Baotou Medical College, Baotou, ChinaInner Mongolia Hospital of Traditional Chinese Medicine, Hohhot, ChinaBaotou Medical College, Baotou, ChinaBaotou Medical College, Baotou, ChinaInner Mongolia Key Laboratory of Characteristic Geoherbs Resources Protection and Utilization, Baotou, ChinaInner Mongolia Key Laboratory of Characteristic Geoherbs Resources Protection and Utilization, Baotou, ChinaDepartment of Pharmacy, Inner Mongolia Medical University, Hohhot, ChinaSchool of Life Sciences, Inner Mongolia University, Hohhot, ChinaBaotou Medical College, Baotou, ChinaBaotou Medical College, Baotou, ChinaInner Mongolia Hospital of Traditional Chinese Medicine, Hohhot, ChinaDepartment of Pharmacy, Inner Mongolia Medical University, Hohhot, ChinaSchool of Life Sciences, Inner Mongolia University, Hohhot, ChinaState Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, ChinaTo provide high-quality Astragalus mongholicus Bunge to domestic and foreign markets and maintain sustainable development of the A. mongholicus industry, Firstly, we evaluated the impact of environmental factors and planting areas on the A. mongholicus industry. The maximum entropy method (MaxEnt) was utilized to simulate the suitability distribution of A. mongholicus and establish the relationship between the active component contents of A. mongholicus and ecological factors through linear regression analysis. The random forest algorithm was subsequently used to perform feature selection and classification extraction on Sentinel-2 imagery covering the study area. Furthermore, the planting, processing, and sales of A. mongholicus in Guyang County were investigated, and the roles of stakeholders in the value chains were analyzed. The results demonstrated that precipitation of the warmest quarter, minimum temperature of the coldest month, standard deviation of seasonal temperature changes, range of mean annual temperature, and mean diurnal range [mean of monthly (max temp - min temp)] were the five environmental variables that contributed the most to the growth of A. mongholicus. The most influential factor on the distribution of high-quality A. mongholicus was the mean temperature of the coldest quarter. The classification results of image features showed that the planting areas of A. mongholicus was consistent with the suitable planting areas predicted by MaxEnt, which can provide data support to the relevant departments for the macro development of the A. mongholicus industry. In the production of A. mongholicus, 10 value chains were constructed, and the study demonstrated that the behavior of stakeholders, target markets, and the selected planting area had a significant impact on the quality of A. mongholicus.https://www.frontiersin.org/articles/10.3389/fpls.2022.908114/fullAstragalus mongholicus Bungevalue chainsspecies distribution modelsmaximum entropyremote sensingrandom forest |
| spellingShingle | Ru Zhang Ru Zhang Mingxu Zhang Yumei Yan Yuan Chen Linlin Jiang Xinxin Wei Xiaobo Zhang Huanting Li Minhui Li Minhui Li Minhui Li Minhui Li Minhui Li Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing Frontiers in Plant Science Astragalus mongholicus Bunge value chains species distribution models maximum entropy remote sensing random forest |
| title | Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing |
| title_full | Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing |
| title_fullStr | Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing |
| title_full_unstemmed | Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing |
| title_short | Promoting the Development of Astragalus mongholicus Bunge Industry in Guyang County (China) Based on MaxEnt and Remote Sensing |
| title_sort | promoting the development of astragalus mongholicus bunge industry in guyang county china based on maxent and remote sensing |
| topic | Astragalus mongholicus Bunge value chains species distribution models maximum entropy remote sensing random forest |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2022.908114/full |
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