Research on a UAV spray system combined with grid atomized droplets
BackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide us...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Plant Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2023.1286332/full |
| _version_ | 1797367746991751168 |
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| author | Xiuyun Xue Xiuyun Xue Xiuyun Xue Xiuyun Xue Yu Tian Zhenyu Yang Zhen Li Zhen Li Zhen Li Zhen Li Shilei Lyu Shilei Lyu Shilei Lyu Shilei Lyu Shuran Song Shuran Song Shuran Song Daozong Sun Daozong Sun Daozong Sun |
| author_facet | Xiuyun Xue Xiuyun Xue Xiuyun Xue Xiuyun Xue Yu Tian Zhenyu Yang Zhen Li Zhen Li Zhen Li Zhen Li Shilei Lyu Shilei Lyu Shilei Lyu Shilei Lyu Shuran Song Shuran Song Shuran Song Daozong Sun Daozong Sun Daozong Sun |
| author_sort | Xiuyun Xue |
| collection | DOAJ |
| description | BackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology.MethodsIn order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method.Results and discussionThis study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error. |
| first_indexed | 2024-03-08T17:22:37Z |
| format | Article |
| id | doaj.art-5361aceab4464b148ed19cb66e40a7ad |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-03-08T17:22:37Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-5361aceab4464b148ed19cb66e40a7ad2024-01-03T04:20:05ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2024-01-011410.3389/fpls.2023.12863321286332Research on a UAV spray system combined with grid atomized dropletsXiuyun Xue0Xiuyun Xue1Xiuyun Xue2Xiuyun Xue3Yu Tian4Zhenyu Yang5Zhen Li6Zhen Li7Zhen Li8Zhen Li9Shilei Lyu10Shilei Lyu11Shilei Lyu12Shilei Lyu13Shuran Song14Shuran Song15Shuran Song16Daozong Sun17Daozong Sun18Daozong Sun19College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaDivision of Citrus Machinery, China Agriculture Research System of Ministry of Finance the People 's Republic of China and Ministry of Agriculture and Rural Affairs of the People 's Republic of China, Guangzhou, ChinaGuangdong Provincial Agricultural Information Monitoring Engineering Technology Research Center, Guangzhou, ChinaPazhou Lab, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaDivision of Citrus Machinery, China Agriculture Research System of Ministry of Finance the People 's Republic of China and Ministry of Agriculture and Rural Affairs of the People 's Republic of China, Guangzhou, ChinaGuangdong Provincial Agricultural Information Monitoring Engineering Technology Research Center, Guangzhou, ChinaPazhou Lab, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaDivision of Citrus Machinery, China Agriculture Research System of Ministry of Finance the People 's Republic of China and Ministry of Agriculture and Rural Affairs of the People 's Republic of China, Guangzhou, ChinaGuangdong Provincial Agricultural Information Monitoring Engineering Technology Research Center, Guangzhou, ChinaPazhou Lab, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaDivision of Citrus Machinery, China Agriculture Research System of Ministry of Finance the People 's Republic of China and Ministry of Agriculture and Rural Affairs of the People 's Republic of China, Guangzhou, ChinaGuangdong Provincial Agricultural Information Monitoring Engineering Technology Research Center, Guangzhou, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, ChinaDivision of Citrus Machinery, China Agriculture Research System of Ministry of Finance the People 's Republic of China and Ministry of Agriculture and Rural Affairs of the People 's Republic of China, Guangzhou, ChinaGuangdong Provincial Agricultural Information Monitoring Engineering Technology Research Center, Guangzhou, ChinaBackgroundsUAVs for crop protection hold significant potential for application in mountainous orchard areas in China. However, certain issues pertaining to UAV spraying need to be addressed for further technological advancement, aimed at enhancing crop protection efficiency and reducing pesticide usage. These challenges include the potential for droplet drift, limited capacity for pesticide solution. Consequently, efforts are required to overcome these limitations and optimize UAV spraying technology.MethodsIn order to balance high deposition and low drift in plant protection UAV spraying, this study proposes a plant protection UAV spraying method. In order to study the operational effects of this spraying method, this study conducted a UAV spray and grid impact test to investigate the effects of different operational parameters on droplet deposition and drift. Meanwhile, a spray model was constructed using machine learning techniques to predict the spraying effect of this method.Results and discussionThis study investigated the droplet deposition rate and downwind drift rate on three types of citrus trees: traditional densely planted trees, dwarf trees, and hedged trees, considering different particle sizes and UAV flight altitudes. Analyzing the effect of increasing the grid on droplet coverage and deposition density for different tree forms. The findings demonstrated a significantly improved droplet deposition rate on dwarf and hedged citrus trees compared to traditional densely planted trees and adopting a fixed-height grid increased droplet coverage and deposition density for both the densely planted and trellised citrus trees, but had the opposite effect on dwarfed citrus trees. When using the grid system. Among the factors examined, the height of the sampling point exhibited the greatest influence on the droplet deposition rate, whereas UAV flight height and droplet particle size had no significant impact. The distance in relation to wind direction had the most substantial effect on droplet drift rate. In terms of predicting droplet drift rate, the BP neural network performed inadequately with a coefficient of determination of 0.88. Conversely, REGRESS, ELM, and RBFNN yielded similar and notably superior results with a coefficient of determination greater than 0.95. Notably, ELM demonstrated the smallest root mean square error.https://www.frontiersin.org/articles/10.3389/fpls.2023.1286332/fullgrid atomizationagricultural unmanned aerial vehicledroplet driftdeposition effectmachine learning prediction |
| spellingShingle | Xiuyun Xue Xiuyun Xue Xiuyun Xue Xiuyun Xue Yu Tian Zhenyu Yang Zhen Li Zhen Li Zhen Li Zhen Li Shilei Lyu Shilei Lyu Shilei Lyu Shilei Lyu Shuran Song Shuran Song Shuran Song Daozong Sun Daozong Sun Daozong Sun Research on a UAV spray system combined with grid atomized droplets Frontiers in Plant Science grid atomization agricultural unmanned aerial vehicle droplet drift deposition effect machine learning prediction |
| title | Research on a UAV spray system combined with grid atomized droplets |
| title_full | Research on a UAV spray system combined with grid atomized droplets |
| title_fullStr | Research on a UAV spray system combined with grid atomized droplets |
| title_full_unstemmed | Research on a UAV spray system combined with grid atomized droplets |
| title_short | Research on a UAV spray system combined with grid atomized droplets |
| title_sort | research on a uav spray system combined with grid atomized droplets |
| topic | grid atomization agricultural unmanned aerial vehicle droplet drift deposition effect machine learning prediction |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1286332/full |
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