Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1783451231883100160 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6743168 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT zangziyi terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents AT wangjie terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents AT cuihongliang terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents AT yanshihan terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents |