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Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management

Rice is one of the three major crops in the world and is the major crop in Asia. Climate change and water resource shortages may result in decreases in rice yields and possible food shortage crises. In this study, water-saving farming management was tested, and IOT field water level monitoring was u...

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Autores principales: Yang, Chin-Ying, Yang, Ming-Der, Tseng, Wei-Cheng, Hsu, Yu-Chun, Li, Guan-Sin, Lai, Ming-Hsin, Wu, Dong-Hong, Lu, Hsiu-Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571168/
https://www.ncbi.nlm.nih.gov/pubmed/32962121
http://dx.doi.org/10.3390/s20185354
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author Yang, Chin-Ying
Yang, Ming-Der
Tseng, Wei-Cheng
Hsu, Yu-Chun
Li, Guan-Sin
Lai, Ming-Hsin
Wu, Dong-Hong
Lu, Hsiu-Ying
author_facet Yang, Chin-Ying
Yang, Ming-Der
Tseng, Wei-Cheng
Hsu, Yu-Chun
Li, Guan-Sin
Lai, Ming-Hsin
Wu, Dong-Hong
Lu, Hsiu-Ying
author_sort Yang, Chin-Ying
collection PubMed
description Rice is one of the three major crops in the world and is the major crop in Asia. Climate change and water resource shortages may result in decreases in rice yields and possible food shortage crises. In this study, water-saving farming management was tested, and IOT field water level monitoring was used to regulate water inflow automatically. Plant height (PH) is an important phenotype to be used to determine difference in rice growth periods and yields using water-saving irrigation. An unmanned aerial vehicle (UAV) with an RGB camera captured sequential images of rice fields to estimate rice PH compared with PH measured on site for estimating rice growth stages. The test results, with two crop harvests in 2019, revealed that with adequate image calibration, the correlation coefficient between UAV-PH and field-PH was higher than 0.98, indicating that UAV images can accurately determine rice PH in the field and rice growth phase. The study demonstrated that water-saving farming is effective, decreasing water usage for the first and second crops of 2019 by 53.5% and 21.7%, respectively, without influencing the growth period and final yield. Coupled with an automated irrigation system, rice farming can be adaptive to water shortage situations.
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spelling pubmed-75711682020-10-28 Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management Yang, Chin-Ying Yang, Ming-Der Tseng, Wei-Cheng Hsu, Yu-Chun Li, Guan-Sin Lai, Ming-Hsin Wu, Dong-Hong Lu, Hsiu-Ying Sensors (Basel) Article Rice is one of the three major crops in the world and is the major crop in Asia. Climate change and water resource shortages may result in decreases in rice yields and possible food shortage crises. In this study, water-saving farming management was tested, and IOT field water level monitoring was used to regulate water inflow automatically. Plant height (PH) is an important phenotype to be used to determine difference in rice growth periods and yields using water-saving irrigation. An unmanned aerial vehicle (UAV) with an RGB camera captured sequential images of rice fields to estimate rice PH compared with PH measured on site for estimating rice growth stages. The test results, with two crop harvests in 2019, revealed that with adequate image calibration, the correlation coefficient between UAV-PH and field-PH was higher than 0.98, indicating that UAV images can accurately determine rice PH in the field and rice growth phase. The study demonstrated that water-saving farming is effective, decreasing water usage for the first and second crops of 2019 by 53.5% and 21.7%, respectively, without influencing the growth period and final yield. Coupled with an automated irrigation system, rice farming can be adaptive to water shortage situations. MDPI 2020-09-18 /pmc/articles/PMC7571168/ /pubmed/32962121 http://dx.doi.org/10.3390/s20185354 Text en © 2020 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
Yang, Chin-Ying
Yang, Ming-Der
Tseng, Wei-Cheng
Hsu, Yu-Chun
Li, Guan-Sin
Lai, Ming-Hsin
Wu, Dong-Hong
Lu, Hsiu-Ying
Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title_full Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title_fullStr Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title_full_unstemmed Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title_short Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management
title_sort assessment of rice developmental stage using time series uav imagery for variable irrigation management
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571168/
https://www.ncbi.nlm.nih.gov/pubmed/32962121
http://dx.doi.org/10.3390/s20185354
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