Investigating the microstructure of plant leaves in 3D with lab-based X-ray Computed Tomography

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

A meta-analysis of mesophyll conductance to CO2in relation to major abiotic stresses in poplar species

Mesophyll conductance (gm) determines the diffusion of CO2 from the substomatal cavities to the site of carboxylation in the chloroplasts and represents a critical component of the diffusive limitation of photosynthesis. In this study, we evaluated the average effect sizes of different environmental constraints on gm in Populus spp., a forest tree model. We collected raw data of 815 A-Ci response curves from 26 datasets to estimate gm, using a single curve-fitting method to alleviate method-related bias. We performed a meta-analysis to assess the effects of different abiotic stresses on gm. We found a significant increase in gm from the bottom to the top of the canopy that was concomitant with the increase of maximum rate of carboxylation and light-saturated photosynthetic rate (Amax). gm was positively associated with increases in soil moisture and nutrient availability, but was insensitive to increasing soil copper concentration and did not vary with atmospheric CO2 concentration. Our results showed that gm was strongly related to Amax and to a lesser extent to stomatal conductance (gs). Moreover, a negative exponential relationship was obtained between gm and specific leaf area, which may be used to scale-up gm within the canopy