RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index
Sugarcane crops have a long cycle with successive harvests before re-planting, and row gaps are one of the main problems associated with the yield. The objective of this study was to establish an alternative methodology for measuring the planting and regrowth of sugarcane rows using UAV (Unmanned Ae...
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2025-01-01
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author | Camila G. B. de Melo Mário M. Rolim Roberta Q. Cavalcanti Marcos V. da Silva Ana Lúcia B. Candeias Pabrício M. O. Lopes Pedro F. S. Ortiz Renato P. de Lima |
author_facet | Camila G. B. de Melo Mário M. Rolim Roberta Q. Cavalcanti Marcos V. da Silva Ana Lúcia B. Candeias Pabrício M. O. Lopes Pedro F. S. Ortiz Renato P. de Lima |
author_sort | Camila G. B. de Melo |
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description | Sugarcane crops have a long cycle with successive harvests before re-planting, and row gaps are one of the main problems associated with the yield. The objective of this study was to establish an alternative methodology for measuring the planting and regrowth of sugarcane rows using UAV (Unmanned Aerial Vehicle) images and to compare it with manual measurements. This study was conducted in a 1 ha experimental area under mechanized harvesting. The reference methodology consists of measuring the continuous distances without regrowth between two plants along a planting row, considering distances greater than 0.50 m as gaps and the following gaps classes: >0.5–1.0 m, >1.0–1.5 m, >1.5–2.0 m, >2.0–3.5 m, and >3.5 m. Images were collected from a UAV equipped with a 12-megapixel RGB camera. The number of regrowth gaps measured through imaging for the class of gaps with a length between 0.5 and 1.0 m was eight times higher than field measurement. In the class of gaps with a length between 1.0 and 1.5 m, the result is the opposite, as the field measurement was approximately three times higher than the UAV measurement, with a significant difference in both classes. In the other length classes analyzed, the number of gaps did not show significant differences. Our results suggest that regrowth gaps can be quickly estimated with the proposed methodology for gaps greater than 1.5 m. For gaps smaller than <1 m, the methodology using a UAV is not accurate. |
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language | English |
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spelling | doaj-art-d32a1e6a86f6461cb1a0853e9c2e9c222025-01-24T13:16:15ZengMDPI AGAgriEngineering2624-74022025-01-01711710.3390/agriengineering7010017RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical IndexCamila G. B. de Melo0Mário M. Rolim1Roberta Q. Cavalcanti2Marcos V. da Silva3Ana Lúcia B. Candeias4Pabrício M. O. Lopes5Pedro F. S. Ortiz6Renato P. de Lima7Department of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171900, PE, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171900, PE, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171900, PE, BrazilDepartment of Agricultural Engineering, Center for Agricultural and Environmental Sciences (CCAA), Federal University of Maranhão, BR-222, Chapadinha 65500000, MA, BrazilDepartment of Cartographic Engineering, Federal University of Pernambuco, Recife 50740530, PE, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171900, PE, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171900, PE, BrazilAgricultural Engineering College, Universidade Estadual de Campinas (UNICAMP), Campinas 13083875, SP, BrazilSugarcane crops have a long cycle with successive harvests before re-planting, and row gaps are one of the main problems associated with the yield. The objective of this study was to establish an alternative methodology for measuring the planting and regrowth of sugarcane rows using UAV (Unmanned Aerial Vehicle) images and to compare it with manual measurements. This study was conducted in a 1 ha experimental area under mechanized harvesting. The reference methodology consists of measuring the continuous distances without regrowth between two plants along a planting row, considering distances greater than 0.50 m as gaps and the following gaps classes: >0.5–1.0 m, >1.0–1.5 m, >1.5–2.0 m, >2.0–3.5 m, and >3.5 m. Images were collected from a UAV equipped with a 12-megapixel RGB camera. The number of regrowth gaps measured through imaging for the class of gaps with a length between 0.5 and 1.0 m was eight times higher than field measurement. In the class of gaps with a length between 1.0 and 1.5 m, the result is the opposite, as the field measurement was approximately three times higher than the UAV measurement, with a significant difference in both classes. In the other length classes analyzed, the number of gaps did not show significant differences. Our results suggest that regrowth gaps can be quickly estimated with the proposed methodology for gaps greater than 1.5 m. For gaps smaller than <1 m, the methodology using a UAV is not accurate.https://www.mdpi.com/2624-7402/7/1/17UAVmechanized harvestingprecision agriculture |
spellingShingle | Camila G. B. de Melo Mário M. Rolim Roberta Q. Cavalcanti Marcos V. da Silva Ana Lúcia B. Candeias Pabrício M. O. Lopes Pedro F. S. Ortiz Renato P. de Lima RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index AgriEngineering UAV mechanized harvesting precision agriculture |
title | RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index |
title_full | RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index |
title_fullStr | RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index |
title_full_unstemmed | RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index |
title_short | RGB Composition Obtained by a UAV in the Monitoring of Sugarcane Row Gaps Using the Biophysical Index |
title_sort | rgb composition obtained by a uav in the monitoring of sugarcane row gaps using the biophysical index |
topic | UAV mechanized harvesting precision agriculture |
url | https://www.mdpi.com/2624-7402/7/1/17 |
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