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Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors,...

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Detalles Bibliográficos
Autores principales: Liu, Tianjiao, Liu, Xiangnan, Liu, Meiling, Wu, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5877332/
https://www.ncbi.nlm.nih.gov/pubmed/29538350
http://dx.doi.org/10.3390/s18030860
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author Liu, Tianjiao
Liu, Xiangnan
Liu, Meiling
Wu, Ling
author_facet Liu, Tianjiao
Liu, Xiangnan
Liu, Meiling
Wu, Ling
author_sort Liu, Tianjiao
collection PubMed
description Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.
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spelling pubmed-58773322018-04-09 Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology Liu, Tianjiao Liu, Xiangnan Liu, Meiling Wu, Ling Sensors (Basel) Article Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice. MDPI 2018-03-14 /pmc/articles/PMC5877332/ /pubmed/29538350 http://dx.doi.org/10.3390/s18030860 Text en © 2018 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
Liu, Tianjiao
Liu, Xiangnan
Liu, Meiling
Wu, Ling
Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title_full Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title_fullStr Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title_full_unstemmed Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title_short Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology
title_sort evaluating heavy metal stress levels in rice based on remote sensing phenology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5877332/
https://www.ncbi.nlm.nih.gov/pubmed/29538350
http://dx.doi.org/10.3390/s18030860
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