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

Abstract 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 t...

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Main Authors: Ziyi Zang, Jie Wang, Hong-Liang Cui, Shihan Yan
Format: Article
Language:English
Published: BMC 2019-09-01
Series:Plant Methods
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13007-019-0492-y
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spelling doaj-050fce13097d46999a5af9ea40ec61162020-11-25T02:41:53ZengBMCPlant Methods1746-48112019-09-0115111110.1186/s13007-019-0492-yTerahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituentsZiyi Zang0Jie Wang1Hong-Liang Cui2Shihan Yan3College of Instrumentation and Electrical Engineering, Jilin UniversityCollege of Instrumentation and Electrical Engineering, Jilin UniversityCollege of Instrumentation and Electrical Engineering, Jilin UniversityChongqing Institute of Green and Intelligent Technology, Chinese Academy of ScienceAbstract 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.http://link.springer.com/article/10.1186/s13007-019-0492-yTerahertz imagingQuantitative analysisPlant leafWater contentSolid matter contentGas content
collection DOAJ
language English
format Article
sources DOAJ
author Ziyi Zang
Jie Wang
Hong-Liang Cui
Shihan Yan
spellingShingle Ziyi Zang
Jie Wang
Hong-Liang Cui
Shihan Yan
Terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
Plant Methods
Terahertz imaging
Quantitative analysis
Plant leaf
Water content
Solid matter content
Gas content
author_facet Ziyi Zang
Jie Wang
Hong-Liang Cui
Shihan Yan
author_sort Ziyi Zang
title 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_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_sort terahertz spectral imaging based quantitative determination of spatial distribution of plant leaf constituents
publisher BMC
series Plant Methods
issn 1746-4811
publishDate 2019-09-01
description Abstract 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.
topic Terahertz imaging
Quantitative analysis
Plant leaf
Water content
Solid matter content
Gas content
url http://link.springer.com/article/10.1186/s13007-019-0492-y
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AT jiewang terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents
AT hongliangcui terahertzspectralimagingbasedquantitativedeterminationofspatialdistributionofplantleafconstituents
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