Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography
Abstract Background Leaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical m...
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doaj-b76e41c933a648a39e6dea0c12a4ef122020-11-25T00:09:54ZengBMCPlant Methods1746-48112018-11-0114111210.1186/s13007-018-0367-7Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomographyAndrew W. Mathers0Christopher Hepworth1Alice L. Baillie2Jen Sloan3Hannah Jones4Marjorie Lundgren5Andrew J. Fleming6Sacha J. Mooney7Craig J. Sturrock8Division of Agricultural and Environmental Sciences, School of Biosciences, University of NottinghamDepartment of Animal and Plant Sciences, University of SheffieldDepartment of Animal and Plant Sciences, University of SheffieldDepartment of Animal and Plant Sciences, University of SheffieldDepartment of Animal and Plant Sciences, University of SheffieldLancaster Environment Centre, Lancaster UniversityDepartment of Animal and Plant Sciences, University of SheffieldDivision of Agricultural and Environmental Sciences, School of Biosciences, University of NottinghamDivision of Agricultural and Environmental Sciences, School of Biosciences, University of NottinghamAbstract Background Leaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical methods of tissue fixation and embedding prior to 2D microscopy of sections is both laborious and susceptible to artefacts that can skew the values obtained. Here we report an image analysis pipeline that provides quantitative descriptors of plant leaf intercellular airspace using lab-based X-ray computed tomography (microCT). We demonstrate successful visualisation and quantification of differences in leaf intercellular airspace in 3D for a range of species (including both dicots and monocots) and provide a comparison with a standard 2D analysis of leaf sections. Results We used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (Smes) for three dicot species (Arabidopsis, tomato and pea) and three monocot grasses (barley, oat and rice). The imaging pipeline consisted of (1) a masking operation to remove the background airspace surrounding the leaf, (2) segmentation by an automated threshold in ImageJ and then (3) quantification of the extracted pores using the ImageJ ‘Analyze Particles’ tool. Arabidopsis had the highest porosity and lowest Smes for the dicot species whereas barley had the highest porosity and the highest Smes for the grass species. Comparison of porosity and Smes estimates from 3D microCT analysis and 2D analysis of sections indicates that both methods provide a comparable estimate of porosity but the 2D method may underestimate Smes by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed. Conclusions Our results demonstrate the utility of high resolution imaging of leaf intercellular airspace networks by lab-based microCT and provide quantitative data on descriptors of leaf cellular architecture. They indicate there is a range of porosity and Smes values in different species and that there is not a simple relationship between these parameters, suggesting the importance of cell size, shape and packing in the determination of cellular parameters proposed to influence leaf photosynthetic performance.http://link.springer.com/article/10.1186/s13007-018-0367-7X-ray computed tomography (microCT)PorosityLeaf structureAir channelsGas exchangePhotosynthesis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andrew W. Mathers Christopher Hepworth Alice L. Baillie Jen Sloan Hannah Jones Marjorie Lundgren Andrew J. Fleming Sacha J. Mooney Craig J. Sturrock |
spellingShingle |
Andrew W. Mathers Christopher Hepworth Alice L. Baillie Jen Sloan Hannah Jones Marjorie Lundgren Andrew J. Fleming Sacha J. Mooney Craig J. Sturrock Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography Plant Methods X-ray computed tomography (microCT) Porosity Leaf structure Air channels Gas exchange Photosynthesis |
author_facet |
Andrew W. Mathers Christopher Hepworth Alice L. Baillie Jen Sloan Hannah Jones Marjorie Lundgren Andrew J. Fleming Sacha J. Mooney Craig J. Sturrock |
author_sort |
Andrew W. Mathers |
title |
Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography |
title_short |
Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography |
title_full |
Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography |
title_fullStr |
Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography |
title_full_unstemmed |
Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography |
title_sort |
investigating the microstructure of plant leaves in 3d with lab-based x-ray computed tomography |
publisher |
BMC |
series |
Plant Methods |
issn |
1746-4811 |
publishDate |
2018-11-01 |
description |
Abstract Background Leaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical methods of tissue fixation and embedding prior to 2D microscopy of sections is both laborious and susceptible to artefacts that can skew the values obtained. Here we report an image analysis pipeline that provides quantitative descriptors of plant leaf intercellular airspace using lab-based X-ray computed tomography (microCT). We demonstrate successful visualisation and quantification of differences in leaf intercellular airspace in 3D for a range of species (including both dicots and monocots) and provide a comparison with a standard 2D analysis of leaf sections. Results We used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (Smes) for three dicot species (Arabidopsis, tomato and pea) and three monocot grasses (barley, oat and rice). The imaging pipeline consisted of (1) a masking operation to remove the background airspace surrounding the leaf, (2) segmentation by an automated threshold in ImageJ and then (3) quantification of the extracted pores using the ImageJ ‘Analyze Particles’ tool. Arabidopsis had the highest porosity and lowest Smes for the dicot species whereas barley had the highest porosity and the highest Smes for the grass species. Comparison of porosity and Smes estimates from 3D microCT analysis and 2D analysis of sections indicates that both methods provide a comparable estimate of porosity but the 2D method may underestimate Smes by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed. Conclusions Our results demonstrate the utility of high resolution imaging of leaf intercellular airspace networks by lab-based microCT and provide quantitative data on descriptors of leaf cellular architecture. They indicate there is a range of porosity and Smes values in different species and that there is not a simple relationship between these parameters, suggesting the importance of cell size, shape and packing in the determination of cellular parameters proposed to influence leaf photosynthetic performance. |
topic |
X-ray computed tomography (microCT) Porosity Leaf structure Air channels Gas exchange Photosynthesis |
url |
http://link.springer.com/article/10.1186/s13007-018-0367-7 |
work_keys_str_mv |
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