Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios
The feasibility of automated individual crop plant care in vegetable crop fields has increased, resulting in improved efficiency and economic benefits. A systems-based approach is a key feature in the engineering design of mechanization that incorporates precision sensing techniques. The objective o...
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| Format: | Article |
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MDPI AG
2017-05-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/17/5/1096 |
| _version_ | 1811302312429223936 |
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| author | Jorge Martínez-Guanter Miguel Garrido-Izard Constantino Valero David C. Slaughter Manuel Pérez-Ruiz |
| author_facet | Jorge Martínez-Guanter Miguel Garrido-Izard Constantino Valero David C. Slaughter Manuel Pérez-Ruiz |
| author_sort | Jorge Martínez-Guanter |
| collection | DOAJ |
| description | The feasibility of automated individual crop plant care in vegetable crop fields has increased, resulting in improved efficiency and economic benefits. A systems-based approach is a key feature in the engineering design of mechanization that incorporates precision sensing techniques. The objective of this study was to design new sensing capabilities to measure crop plant spacing under different test conditions (California, USA and Andalucía, Spain). For this study, three different types of optical sensors were used: an optical light-beam sensor (880 nm), a Light Detection and Ranging (LiDAR) sensor (905 nm), and an RGB camera. Field trials were conducted on newly transplanted tomato plants, using an encoder as a local reference system. Test results achieved a 98% accuracy in detection using light-beam sensors while a 96% accuracy on plant detections was achieved in the best of replications using LiDAR. These results can contribute to the decision-making regarding the use of these sensors by machinery manufacturers. This could lead to an advance in the physical or chemical weed control on row crops, allowing significant reductions or even elimination of hand-weeding tasks. |
| first_indexed | 2024-04-13T07:25:49Z |
| format | Article |
| id | doaj.art-8b6cd54acb5346d98c1b8286ce6dcc21 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:25:49Z |
| publishDate | 2017-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8b6cd54acb5346d98c1b8286ce6dcc212022-12-22T02:56:29ZengMDPI AGSensors1424-82202017-05-01175109610.3390/s17051096s17051096Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two ScenariosJorge Martínez-Guanter0Miguel Garrido-Izard1Constantino Valero2David C. Slaughter3Manuel Pérez-Ruiz4Aerospace Engineering and Fluid Mechanics Department, University of Seville, 41013 Seville, SpainLaboratorio de Propiedades Físicas (LPF_TAGRALIA), Universidad Politécnica de Madrid (UPM), 28040 Madrid, SpainLaboratorio de Propiedades Físicas (LPF_TAGRALIA), Universidad Politécnica de Madrid (UPM), 28040 Madrid, SpainDepartment of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USAAerospace Engineering and Fluid Mechanics Department, University of Seville, 41013 Seville, SpainThe feasibility of automated individual crop plant care in vegetable crop fields has increased, resulting in improved efficiency and economic benefits. A systems-based approach is a key feature in the engineering design of mechanization that incorporates precision sensing techniques. The objective of this study was to design new sensing capabilities to measure crop plant spacing under different test conditions (California, USA and Andalucía, Spain). For this study, three different types of optical sensors were used: an optical light-beam sensor (880 nm), a Light Detection and Ranging (LiDAR) sensor (905 nm), and an RGB camera. Field trials were conducted on newly transplanted tomato plants, using an encoder as a local reference system. Test results achieved a 98% accuracy in detection using light-beam sensors while a 96% accuracy on plant detections was achieved in the best of replications using LiDAR. These results can contribute to the decision-making regarding the use of these sensors by machinery manufacturers. This could lead to an advance in the physical or chemical weed control on row crops, allowing significant reductions or even elimination of hand-weeding tasks.http://www.mdpi.com/1424-8220/17/5/1096LiDARlight-beamplant localizationKinect |
| spellingShingle | Jorge Martínez-Guanter Miguel Garrido-Izard Constantino Valero David C. Slaughter Manuel Pérez-Ruiz Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios Sensors LiDAR light-beam plant localization Kinect |
| title | Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
| title_full | Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
| title_fullStr | Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
| title_full_unstemmed | Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
| title_short | Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
| title_sort | optical sensing to determine tomato plant spacing for precise agrochemical application two scenarios |
| topic | LiDAR light-beam plant localization Kinect |
| url | http://www.mdpi.com/1424-8220/17/5/1096 |
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