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FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform
Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239877/ https://www.ncbi.nlm.nih.gov/pubmed/25302811 http://dx.doi.org/10.3390/s141018650 |
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author | Duarte-Galvan, Carlos de J. Romero-Troncoso, Rene Torres-Pacheco, Irineo Guevara-Gonzalez, Ramon G. Fernandez-Jaramillo, Arturo A. Contreras-Medina, Luis M. Carrillo-Serrano, Roberto V. Millan-Almaraz, Jesus R. |
author_facet | Duarte-Galvan, Carlos de J. Romero-Troncoso, Rene Torres-Pacheco, Irineo Guevara-Gonzalez, Ramon G. Fernandez-Jaramillo, Arturo A. Contreras-Medina, Luis M. Carrillo-Serrano, Roberto V. Millan-Almaraz, Jesus R. |
author_sort | Duarte-Galvan, Carlos |
collection | PubMed |
description | Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions. |
format | Online Article Text |
id | pubmed-4239877 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-42398772014-11-21 FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform Duarte-Galvan, Carlos de J. Romero-Troncoso, Rene Torres-Pacheco, Irineo Guevara-Gonzalez, Ramon G. Fernandez-Jaramillo, Arturo A. Contreras-Medina, Luis M. Carrillo-Serrano, Roberto V. Millan-Almaraz, Jesus R. Sensors (Basel) Article Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions. MDPI 2014-10-09 /pmc/articles/PMC4239877/ /pubmed/25302811 http://dx.doi.org/10.3390/s141018650 Text en © 2014 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 license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Duarte-Galvan, Carlos de J. Romero-Troncoso, Rene Torres-Pacheco, Irineo Guevara-Gonzalez, Ramon G. Fernandez-Jaramillo, Arturo A. Contreras-Medina, Luis M. Carrillo-Serrano, Roberto V. Millan-Almaraz, Jesus R. FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title | FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title_full | FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title_fullStr | FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title_full_unstemmed | FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title_short | FPGA-Based Smart Sensor for Drought Stress Detection in Tomato Plants Using Novel Physiological Variables and Discrete Wavelet Transform |
title_sort | fpga-based smart sensor for drought stress detection in tomato plants using novel physiological variables and discrete wavelet transform |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239877/ https://www.ncbi.nlm.nih.gov/pubmed/25302811 http://dx.doi.org/10.3390/s141018650 |
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