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Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Andrew Mathers
  • Christopher Hepworth
  • Alice L. Baillie
  • Jen Sloan
  • Hannah Jones
  • Marjorie Ruth Lundgren
  • Andrew J. Fleming
  • Sacha J. Mooney
  • Craig J. Sturrock
Article number99
<mark>Journal publication date</mark>12/11/2018
<mark>Journal</mark>Plant Methods
Issue number1
Number of pages12
Publication StatusPublished
<mark>Original language</mark>English


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. © 2018 The Author(s).

Bibliographic note

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