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Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing
Precision Irrigation (PI) is a promising technique for monitoring and controlling water use that allows for meeting crop water requirements based on site-specific data. However, implementing the PI needs precise data on water evapotranspiration. The detection and monitoring of crop water stress can...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919097/ https://www.ncbi.nlm.nih.gov/pubmed/36772359 http://dx.doi.org/10.3390/s23031318 |
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author | de Paulo, Rodrigo Leme Garcia, Angel Pontin Umezu, Claudio Kiyoshi de Camargo, Antonio Pires Soares, Fabrício Theodoro Albiero, Daniel |
author_facet | de Paulo, Rodrigo Leme Garcia, Angel Pontin Umezu, Claudio Kiyoshi de Camargo, Antonio Pires Soares, Fabrício Theodoro Albiero, Daniel |
author_sort | de Paulo, Rodrigo Leme |
collection | PubMed |
description | Precision Irrigation (PI) is a promising technique for monitoring and controlling water use that allows for meeting crop water requirements based on site-specific data. However, implementing the PI needs precise data on water evapotranspiration. The detection and monitoring of crop water stress can be achieved by several methods, one of the most interesting being the use of infra-red (IR) thermometry combined with the estimate of the Crop Water Stress Index (CWSI). However, conventional IR equipment is expensive, so the objective of this paper is to present the development of a new low-cost water stress detection system using TL indices obtained by crossing the responses of infrared sensors with image processing. The results demonstrated that it is possible to use low-cost IR sensors with a directional Field of Vision (FoV) to measure plant temperature, generate thermal maps, and identify water stress conditions. The Leaf Temperature Maps, generated by the IR sensor readings of the plant segmentation in the RGB image, were validated by thermal images. Furthermore, the estimated CWSI is consistent with the literature results. |
format | Online Article Text |
id | pubmed-9919097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99190972023-02-12 Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing de Paulo, Rodrigo Leme Garcia, Angel Pontin Umezu, Claudio Kiyoshi de Camargo, Antonio Pires Soares, Fabrício Theodoro Albiero, Daniel Sensors (Basel) Article Precision Irrigation (PI) is a promising technique for monitoring and controlling water use that allows for meeting crop water requirements based on site-specific data. However, implementing the PI needs precise data on water evapotranspiration. The detection and monitoring of crop water stress can be achieved by several methods, one of the most interesting being the use of infra-red (IR) thermometry combined with the estimate of the Crop Water Stress Index (CWSI). However, conventional IR equipment is expensive, so the objective of this paper is to present the development of a new low-cost water stress detection system using TL indices obtained by crossing the responses of infrared sensors with image processing. The results demonstrated that it is possible to use low-cost IR sensors with a directional Field of Vision (FoV) to measure plant temperature, generate thermal maps, and identify water stress conditions. The Leaf Temperature Maps, generated by the IR sensor readings of the plant segmentation in the RGB image, were validated by thermal images. Furthermore, the estimated CWSI is consistent with the literature results. MDPI 2023-01-24 /pmc/articles/PMC9919097/ /pubmed/36772359 http://dx.doi.org/10.3390/s23031318 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article de Paulo, Rodrigo Leme Garcia, Angel Pontin Umezu, Claudio Kiyoshi de Camargo, Antonio Pires Soares, Fabrício Theodoro Albiero, Daniel Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title | Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title_full | Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title_fullStr | Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title_full_unstemmed | Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title_short | Water Stress Index Detection Using a Low-Cost Infrared Sensor and Excess Green Image Processing |
title_sort | water stress index detection using a low-cost infrared sensor and excess green image processing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919097/ https://www.ncbi.nlm.nih.gov/pubmed/36772359 http://dx.doi.org/10.3390/s23031318 |
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