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Real-Time Assessment of Mandarin Crop Water Stress Index
The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185456/ https://www.ncbi.nlm.nih.gov/pubmed/35684639 http://dx.doi.org/10.3390/s22114018 |
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author | Appiah, Sadick Amoakohene Li, Jiuhao Lan, Yubin Darko, Ransford Opoku Alordzinu, Kelvin Edom Al Aasmi, Alaa Asenso, Evans Issaka, Fuseini Afful, Ebenezer Acheampong Wang, Hao Qiao, Songyang |
author_facet | Appiah, Sadick Amoakohene Li, Jiuhao Lan, Yubin Darko, Ransford Opoku Alordzinu, Kelvin Edom Al Aasmi, Alaa Asenso, Evans Issaka, Fuseini Afful, Ebenezer Acheampong Wang, Hao Qiao, Songyang |
author_sort | Appiah, Sadick Amoakohene |
collection | PubMed |
description | The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level of water stress in plants continuously and to provide automatic sensing and controls. This research aimed at determining the viability, efficiency, and swiftness in employing the commercial Workswell WIRIS Agro R infrared camera (WWARIC) in monitoring water stress and scheduling appropriate irrigation regimes in mandarin plants. The experiment used a four-by-three randomized complete block design with 80–100% FC water treatment as full field capacity and three deficit irrigation treatments at 70–75% FC, 60–65% FC, and 50–55% FC. Air temperature, canopy temperature, and vapor pressure deficits were measured and employed to deduce the empirical crop water stress index, using the Idso approach (CWSI((Idso))) as well as baseline equations to calculate non-water stress and water stressed conditions. The relative leaf water content (RLWC) of mandarin plants was also determined for the growing season. From the experiment, CWSI((Idso)) and CWSI were estimated using the Workswell Wiris Agro R infrared camera (CWSI(W)) and showed a high correlation (R(2) = 0.75 at p < 0.05) in assessing the extent of water stress in mandarin plants. The results also showed that at an altitude of 12 m above the mandarin canopy, the WWARIC was able to identify water stress using three modes (empirical, differential, and theoretical). The WWARIC’s color map feature, presented in real time, makes the camera a suitable device, as there is no need for complex computations or expert advice before determining the extent of the stress the crops are subjected to. The results prove that this novel use of the WWARIC demonstrated sufficient precision, swiftness, and intelligibility in the real-time detection of the mandarin water stress index and, accordingly, assisted in scheduling irrigation. |
format | Online Article Text |
id | pubmed-9185456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91854562022-06-11 Real-Time Assessment of Mandarin Crop Water Stress Index Appiah, Sadick Amoakohene Li, Jiuhao Lan, Yubin Darko, Ransford Opoku Alordzinu, Kelvin Edom Al Aasmi, Alaa Asenso, Evans Issaka, Fuseini Afful, Ebenezer Acheampong Wang, Hao Qiao, Songyang Sensors (Basel) Article The use of plant-based indicators and other conventional means to detect the level of water stress in crops may be challenging, due to their difficulties in automation, their arduousness, and their time-consuming nature. Non-contact and non-destructive sensing methods can be used to detect the level of water stress in plants continuously and to provide automatic sensing and controls. This research aimed at determining the viability, efficiency, and swiftness in employing the commercial Workswell WIRIS Agro R infrared camera (WWARIC) in monitoring water stress and scheduling appropriate irrigation regimes in mandarin plants. The experiment used a four-by-three randomized complete block design with 80–100% FC water treatment as full field capacity and three deficit irrigation treatments at 70–75% FC, 60–65% FC, and 50–55% FC. Air temperature, canopy temperature, and vapor pressure deficits were measured and employed to deduce the empirical crop water stress index, using the Idso approach (CWSI((Idso))) as well as baseline equations to calculate non-water stress and water stressed conditions. The relative leaf water content (RLWC) of mandarin plants was also determined for the growing season. From the experiment, CWSI((Idso)) and CWSI were estimated using the Workswell Wiris Agro R infrared camera (CWSI(W)) and showed a high correlation (R(2) = 0.75 at p < 0.05) in assessing the extent of water stress in mandarin plants. The results also showed that at an altitude of 12 m above the mandarin canopy, the WWARIC was able to identify water stress using three modes (empirical, differential, and theoretical). The WWARIC’s color map feature, presented in real time, makes the camera a suitable device, as there is no need for complex computations or expert advice before determining the extent of the stress the crops are subjected to. The results prove that this novel use of the WWARIC demonstrated sufficient precision, swiftness, and intelligibility in the real-time detection of the mandarin water stress index and, accordingly, assisted in scheduling irrigation. MDPI 2022-05-26 /pmc/articles/PMC9185456/ /pubmed/35684639 http://dx.doi.org/10.3390/s22114018 Text en © 2022 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 Appiah, Sadick Amoakohene Li, Jiuhao Lan, Yubin Darko, Ransford Opoku Alordzinu, Kelvin Edom Al Aasmi, Alaa Asenso, Evans Issaka, Fuseini Afful, Ebenezer Acheampong Wang, Hao Qiao, Songyang Real-Time Assessment of Mandarin Crop Water Stress Index |
title | Real-Time Assessment of Mandarin Crop Water Stress Index |
title_full | Real-Time Assessment of Mandarin Crop Water Stress Index |
title_fullStr | Real-Time Assessment of Mandarin Crop Water Stress Index |
title_full_unstemmed | Real-Time Assessment of Mandarin Crop Water Stress Index |
title_short | Real-Time Assessment of Mandarin Crop Water Stress Index |
title_sort | real-time assessment of mandarin crop water stress index |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185456/ https://www.ncbi.nlm.nih.gov/pubmed/35684639 http://dx.doi.org/10.3390/s22114018 |
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