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Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy

Increases in the frequency and severity of droughts across many regions worldwide necessitate an improved capacity to determine the water status of plants at organ, whole plant, canopy, and regional scales. Noninvasive methods have most potential for simultaneously improving basic water relations re...

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Autores principales: Browne, Marvin, Yardimci, Nezih Tolga, Scoffoni, Christine, Jarrahi, Mona, Sack, Lawren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164375/
https://www.ncbi.nlm.nih.gov/pubmed/32313868
http://dx.doi.org/10.1002/pld3.197
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author Browne, Marvin
Yardimci, Nezih Tolga
Scoffoni, Christine
Jarrahi, Mona
Sack, Lawren
author_facet Browne, Marvin
Yardimci, Nezih Tolga
Scoffoni, Christine
Jarrahi, Mona
Sack, Lawren
author_sort Browne, Marvin
collection PubMed
description Increases in the frequency and severity of droughts across many regions worldwide necessitate an improved capacity to determine the water status of plants at organ, whole plant, canopy, and regional scales. Noninvasive methods have most potential for simultaneously improving basic water relations research and ground‐, flight‐, and space‐based sensing of water status, with applications in sustainability, food security, and conservation. The most frequently used methods to measure the most salient proxies of plant water status, that is, water mass per leaf area (WMA), relative water content (RWC), and leaf water potential (Ψ(leaf)), require the excision of tissues and laboratory analysis, and have thus been limited to relatively low throughput and small study scales. Applications using electromagnetic radiation in the visible, infrared, and terahertz ranges can resolve the water status of canopies, yet heretofore have typically focused on statistical approaches to estimating RWC for leaves before and after severe dehydration, and few have predicted Ψ(leaf). Terahertz radiation has great promise to estimate leaf water status across the range of leaf dehydration important for the control of gas exchange and leaf survival. We demonstrate a refined method and physical model to predict WMA, RWC, and Ψ(leaf) from terahertz transmission across a wide range of levels of dehydration for given leaves of three species, as well as across leaves of given species and across multiple species. These findings highlight the powerful potential and the outstanding challenges in applying in vivo terahertz spectrometry as a remote sensor of water status for a range of applications.
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spelling pubmed-71643752020-04-20 Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy Browne, Marvin Yardimci, Nezih Tolga Scoffoni, Christine Jarrahi, Mona Sack, Lawren Plant Direct Original Research Increases in the frequency and severity of droughts across many regions worldwide necessitate an improved capacity to determine the water status of plants at organ, whole plant, canopy, and regional scales. Noninvasive methods have most potential for simultaneously improving basic water relations research and ground‐, flight‐, and space‐based sensing of water status, with applications in sustainability, food security, and conservation. The most frequently used methods to measure the most salient proxies of plant water status, that is, water mass per leaf area (WMA), relative water content (RWC), and leaf water potential (Ψ(leaf)), require the excision of tissues and laboratory analysis, and have thus been limited to relatively low throughput and small study scales. Applications using electromagnetic radiation in the visible, infrared, and terahertz ranges can resolve the water status of canopies, yet heretofore have typically focused on statistical approaches to estimating RWC for leaves before and after severe dehydration, and few have predicted Ψ(leaf). Terahertz radiation has great promise to estimate leaf water status across the range of leaf dehydration important for the control of gas exchange and leaf survival. We demonstrate a refined method and physical model to predict WMA, RWC, and Ψ(leaf) from terahertz transmission across a wide range of levels of dehydration for given leaves of three species, as well as across leaves of given species and across multiple species. These findings highlight the powerful potential and the outstanding challenges in applying in vivo terahertz spectrometry as a remote sensor of water status for a range of applications. John Wiley and Sons Inc. 2020-04-17 /pmc/articles/PMC7164375/ /pubmed/32313868 http://dx.doi.org/10.1002/pld3.197 Text en © 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd. This is an open access article under the terms of thehttp://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Research
Browne, Marvin
Yardimci, Nezih Tolga
Scoffoni, Christine
Jarrahi, Mona
Sack, Lawren
Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title_full Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title_fullStr Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title_full_unstemmed Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title_short Prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
title_sort prediction of leaf water potential and relative water content using terahertz radiation spectroscopy
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164375/
https://www.ncbi.nlm.nih.gov/pubmed/32313868
http://dx.doi.org/10.1002/pld3.197
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