Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision
In agriculture, the plant leaf angle influences light use efficiency and photosynthesis and, consequently, the overall crop performance. Leaf angle measurements are used in plant phenotyping, plant breeding, and remote sensing to study plant function and structure. Traditional manual leaf angle meas...
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| Language: | English |
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Elsevier
2025-06-01
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| Series: | MethodsX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125000172 |
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| author | Frederik Hennecke Jonas Bömer René H.J. Heim |
| author_facet | Frederik Hennecke Jonas Bömer René H.J. Heim |
| author_sort | Frederik Hennecke |
| collection | DOAJ |
| description | In agriculture, the plant leaf angle influences light use efficiency and photosynthesis and, consequently, the overall crop performance. Leaf angle measurements are used in plant phenotyping, plant breeding, and remote sensing to study plant function and structure. Traditional manual leaf angle measurements have limited precision as they are labor- and time-intensive due to challenging environmental conditions and highly dynamic plant processes. To enable more detailed studies on leaf angles, we modified a well-established automated farming robot to obtain high-resolution 3D point clouds at customizable intervals of individual plants using stereo vision. We demonstrate the system's accuracy and reliability, with minimal deviation from reference values. The method can be utilized by other researchers to gather data on leaf angles and other structural plant traits at regular intervals to access the dynamics of leaves, plants, and canopies. The system's low cost and adaptability can enhance the efficiency of crop monitoring in plant breeding and phenotyping experiments. Detailed documentation and code are available on GitHub. • An open-source farming robot is retrofitted to function as an automatic data collection platform • Hard to access leaf angles can be retrieved with high accuracy • Leaf angle dynamics can be observed with high temporal resolution |
| format | Article |
| id | doaj-art-dc1226294dd645088c9cfdd1181e26e3 |
| institution | Kabale University |
| issn | 2215-0161 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj-art-dc1226294dd645088c9cfdd1181e26e32025-01-18T05:04:43ZengElsevierMethodsX2215-01612025-06-0114103169Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo visionFrederik Hennecke0Jonas Bömer1René H.J. Heim2Institute of Computer Science, University of Göttingen, Goldschmidtstr. 7, 37077 Göttingen, GermanyInstitute of Sugar Beet Research, Holtenser Landstraße 77, 37079 Göttingen, GermanyInstitute for Geodesy and Geoinformation, University of Bonn, Nussallee 17, 53115 Bonn, Germany; Institute of Sugar Beet Research, Holtenser Landstraße 77, 37079 Göttingen, Germany; Corresponding author.In agriculture, the plant leaf angle influences light use efficiency and photosynthesis and, consequently, the overall crop performance. Leaf angle measurements are used in plant phenotyping, plant breeding, and remote sensing to study plant function and structure. Traditional manual leaf angle measurements have limited precision as they are labor- and time-intensive due to challenging environmental conditions and highly dynamic plant processes. To enable more detailed studies on leaf angles, we modified a well-established automated farming robot to obtain high-resolution 3D point clouds at customizable intervals of individual plants using stereo vision. We demonstrate the system's accuracy and reliability, with minimal deviation from reference values. The method can be utilized by other researchers to gather data on leaf angles and other structural plant traits at regular intervals to access the dynamics of leaves, plants, and canopies. The system's low cost and adaptability can enhance the efficiency of crop monitoring in plant breeding and phenotyping experiments. Detailed documentation and code are available on GitHub. • An open-source farming robot is retrofitted to function as an automatic data collection platform • Hard to access leaf angles can be retrieved with high accuracy • Leaf angle dynamics can be observed with high temporal resolutionhttp://www.sciencedirect.com/science/article/pii/S2215016125000172Observing temporal leaf angle dynamics by retrofitting an open-source farming robot |
| spellingShingle | Frederik Hennecke Jonas Bömer René H.J. Heim Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision MethodsX Observing temporal leaf angle dynamics by retrofitting an open-source farming robot |
| title | Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| title_full | Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| title_fullStr | Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| title_full_unstemmed | Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| title_short | Modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| title_sort | modification of an automated precision farming robot for high temporal resolution measurement of leaf angle dynamics using stereo vision |
| topic | Observing temporal leaf angle dynamics by retrofitting an open-source farming robot |
| url | http://www.sciencedirect.com/science/article/pii/S2215016125000172 |
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