Literature DB >> 30042212

Beyond Porosity: 3D Leaf Intercellular Airspace Traits That Impact Mesophyll Conductance.

J Mason Earles1, Guillaume Theroux-Rancourt2, Adam B Roddy1, Matthew E Gilbert3, Andrew J McElrone4,5, Craig R Brodersen1.   

Abstract

The leaf intercellular airspace (IAS) is generally considered to have high conductance to CO2 diffusion relative to the liquid phase. While previous studies accounted for leaf-level variation in porosity and mesophyll thickness, they omitted 3D IAS traits that potentially influence IAS conductance (gIAS). Here, we reevaluated the standard equation for gIAS by incorporating tortuosity, lateral path lengthening, and IAS connectivity. We measured and spatially mapped these geometric IAS traits for 19 Bromeliaceae species with Crassulacean acid metabolism (CAM) or C3 photosynthetic pathways using x-ray microcomputed tomography imaging and a novel computational approach. We found substantial variation in porosity (0.04-0.73 m3 m-3), tortuosity (1.09-3.33 m2 m-2), lateral path lengthening (1.12-3.19 m m-1), and IAS connectivity (0.81-0.97 m2 m-2) across all bromeliad leaves. The revised gIAS model predicted significantly lower gIAS in CAM (0.01-0.19 mol m-2 s-1 bar-1) than in C3 (0.41-2.38 mol m-2 s-1 bar-1) plants due to a coordinated decline in these IAS traits. Our reevaluated equation also generally predicted lower gIAS values than the former one. Moreover, we observed high spatial heterogeneity in these IAS geometric traits throughout the mesophyll, especially within CAM leaves. Our data show that IAS traits that better capture the 3D complexity of leaves strongly influence gIAS and that the impact of the IAS on mesophyll conductance should be carefully considered with respect to leaf anatomy. We provide a simple function to estimate tortuosity and lateral path lengthening in the absence of access to imaging tools such as x-ray microcomputed tomography or other novel 3D image-processing techniques.
© 2018 American Society of Plant Biologists. All rights reserved.

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Year:  2018        PMID: 30042212      PMCID: PMC6130031          DOI: 10.1104/pp.18.00550

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  39 in total

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Authors:  D F Parkhurst; K A Mott
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Authors:  J Mason Earles; Guillaume Théroux-Rancourt; Matthew E Gilbert; Andrew J McElrone; Craig R Brodersen
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3.  Digitally deconstructing leaves in 3D using X-ray microcomputed tomography and machine learning.

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5.  Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size.

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6.  In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model.

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7.  Preparation, Scanning and Analysis of Duckweed Using X-Ray Computed Microtomography.

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Review 10.  Riddled with holes: Understanding air space formation in plant leaves.

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