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Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents

BACKGROUND: Plant leaves have heterogeneous structures composed of spatially variable distribution of liquid, solid, and gaseous matter. Such contents and distribution characteristics correlate with the leaf vigor and phylogenic traits. Recently, terahertz (THz) techniques have been proved to access...

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Autores principales: Zang, Ziyi, Wang, Jie, Cui, Hong-Liang, Yan, Shihan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743168/
https://www.ncbi.nlm.nih.gov/pubmed/31528198
http://dx.doi.org/10.1186/s13007-019-0492-y
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author Zang, Ziyi
Wang, Jie
Cui, Hong-Liang
Yan, Shihan
author_facet Zang, Ziyi
Wang, Jie
Cui, Hong-Liang
Yan, Shihan
author_sort Zang, Ziyi
collection PubMed
description BACKGROUND: Plant leaves have heterogeneous structures composed of spatially variable distribution of liquid, solid, and gaseous matter. Such contents and distribution characteristics correlate with the leaf vigor and phylogenic traits. Recently, terahertz (THz) techniques have been proved to access leaf water content and spatial heterogeneity distribution information, but the solid matter content and gas network information were usually ignored, even though they also affect the THz dielectric function of the leaf. RESULTS: A particle swarm optimization algorithm is employed for a one-off quantitative assay of spatial variability distribution of the leaf compositions from THz data, based on an extended Landau–Lifshitz–Looyenga model, and experimentally verified using Bougainvillea spectabilis leaves. A good agreement is demonstrated for water and solid matter contents between the THz-based method and the gravimetric analysis. In particular, the THz-based method shows good sensitivity to fine-grained differences of leaf growth and development stages. Furthermore, such subtle features as damages and wounds in leaf could be discovered through THz detection and comparison regarding spatial heterogeneity of component contents. CONCLUSIONS: This THz imaging method provides quantitative assay of the leaf constituent contents with the spatial distribution feature, which has the potential for applications in crop disease diagnosis and farmland cultivation management.
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spelling pubmed-67431682019-09-16 Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents Zang, Ziyi Wang, Jie Cui, Hong-Liang Yan, Shihan Plant Methods Research BACKGROUND: Plant leaves have heterogeneous structures composed of spatially variable distribution of liquid, solid, and gaseous matter. Such contents and distribution characteristics correlate with the leaf vigor and phylogenic traits. Recently, terahertz (THz) techniques have been proved to access leaf water content and spatial heterogeneity distribution information, but the solid matter content and gas network information were usually ignored, even though they also affect the THz dielectric function of the leaf. RESULTS: A particle swarm optimization algorithm is employed for a one-off quantitative assay of spatial variability distribution of the leaf compositions from THz data, based on an extended Landau–Lifshitz–Looyenga model, and experimentally verified using Bougainvillea spectabilis leaves. A good agreement is demonstrated for water and solid matter contents between the THz-based method and the gravimetric analysis. In particular, the THz-based method shows good sensitivity to fine-grained differences of leaf growth and development stages. Furthermore, such subtle features as damages and wounds in leaf could be discovered through THz detection and comparison regarding spatial heterogeneity of component contents. CONCLUSIONS: This THz imaging method provides quantitative assay of the leaf constituent contents with the spatial distribution feature, which has the potential for applications in crop disease diagnosis and farmland cultivation management. BioMed Central 2019-09-13 /pmc/articles/PMC6743168/ /pubmed/31528198 http://dx.doi.org/10.1186/s13007-019-0492-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zang, Ziyi
Wang, Jie
Cui, Hong-Liang
Yan, Shihan
Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title_full Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title_fullStr Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title_full_unstemmed Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title_short Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
title_sort terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743168/
https://www.ncbi.nlm.nih.gov/pubmed/31528198
http://dx.doi.org/10.1186/s13007-019-0492-y
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