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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470486/ https://www.ncbi.nlm.nih.gov/pubmed/28492504 http://dx.doi.org/10.3390/s17051096 |
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author | Martínez-Guanter, Jorge Garrido-Izard, Miguel Valero, Constantino Slaughter, David C. Pérez-Ruiz, Manuel |
author_facet | Martínez-Guanter, Jorge Garrido-Izard, Miguel Valero, Constantino Slaughter, David C. Pérez-Ruiz, Manuel |
author_sort | Martínez-Guanter, Jorge |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-5470486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54704862017-06-16 Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios Martínez-Guanter, Jorge Garrido-Izard, Miguel Valero, Constantino Slaughter, David C. Pérez-Ruiz, Manuel Sensors (Basel) Article 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. MDPI 2017-05-11 /pmc/articles/PMC5470486/ /pubmed/28492504 http://dx.doi.org/10.3390/s17051096 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Martínez-Guanter, Jorge Garrido-Izard, Miguel Valero, Constantino Slaughter, David C. Pérez-Ruiz, Manuel Optical Sensing to Determine Tomato Plant Spacing for Precise Agrochemical Application: Two Scenarios |
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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470486/ https://www.ncbi.nlm.nih.gov/pubmed/28492504 http://dx.doi.org/10.3390/s17051096 |
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