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      Automatic analysis of the 3-D microstructure of fruit parenchyma tissue using X-ray micro-CT explains differences in aeration

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          Abstract

          Background

          3D high-resolution X-ray imaging methods have emerged over the last years for visualising the anatomy of tissue samples without substantial sample preparation. Quantitative analysis of cells and intercellular spaces in these images has, however, been difficult and was largely based on manual image processing. We present here an automated procedure for processing high-resolution X-ray images of parenchyma tissues of apple ( Malus ×  domestica Borkh.) and pear ( Pyrus communis L.) as a rapid objective method for characterizing 3D plant tissue anatomy at the level of single cells and intercellular spaces.

          Results

          We isolated neighboring cells in 3D images of apple and pear cortex tissues, and constructed a virtual sieve to discard incorrectly segmented cell particles or unseparated clumps of cells. Void networks were stripped down until their essential connectivity features remained. Statistical analysis of structural parameters showed significant differences between genotypes in the void and cell networks that relate to differences in aeration properties of the tissues.

          Conclusions

          A new model for effective oxygen diffusivity of parenchyma tissue is proposed that not only accounts for the tortuosity of interconnected voids, but also for significant diffusion across cells where the void network is not connected. This will significantly aid interpretation and analysis of future tissue aeration studies. The automated image analysis methodology will also support pheno- and genotyping studies where the 3D tissue anatomy plays a role.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12870-015-0650-y) contains supplementary material, which is available to authorized users.

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          Most cited references53

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          Aeration in Higher Plants

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            Cell to whole-plant phenotyping: the best is yet to come.

            Imaging and image processing have revolutionized plant phenotyping and are now a major tool for phenotypic trait measurement. Here we review plant phenotyping systems by examining three important characteristics: throughput, dimensionality, and resolution. First, whole-plant phenotyping systems are highlighted together with advances in automation that enable significant throughput increases. Organ and cellular level phenotyping and its tools, often operating at a lower throughput, are then discussed as a means to obtain high-dimensional phenotypic data at elevated spatial and temporal resolution. The significance of recent developments in sensor technologies that give access to plant morphology and physiology-related traits is shown. Overall, attention is focused on spatial and temporal resolution because these are crucial aspects of imaging procedures in plant phenotyping systems. Copyright © 2013 Elsevier Ltd. All rights reserved.
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              The diffusive tortuosity of fine-grained unlithified sediments

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                Author and article information

                Contributors
                Els.Herremans@biw.kuleuven.be
                pieter.verboven@biw.kuleuven.be
                Bert.Verlinden@biw.kuleuven.be
                Dennis.Cantre@biw.kuleuven.be
                Metadel.Abera@biw.kuleuven.be
                Martine.Wevers@mtm.kuleuven.be
                Bart.Nicolai@biw.kuleuven.be
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                30 October 2015
                30 October 2015
                2015
                : 15
                : 264
                Affiliations
                [ ]BIOSYST-MeBioS, KU Leuven, Willem de Croylaan 42, 3001 Leuven, Belgium
                [ ]Flanders Centre of Postharvest Technology, Willem de Croylaan 42, 3001 Leuven, Belgium
                [ ]MTM, KU Leuven, Kasteelpark Arenberg 44, 3001 Leuven, Belgium
                Article
                650
                10.1186/s12870-015-0650-y
                4628266
                26518365
                e3a85e32-3bbb-4b36-8a16-16f41eb2dbb4
                © Herremans et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 May 2015
                : 21 October 2015
                Categories
                Methodology Article
                Custom metadata
                © The Author(s) 2015

                Plant science & Botany
                image analysis,apple,pear,diffusion,oxygen,gas space,mathematical model,tomography
                Plant science & Botany
                image analysis, apple, pear, diffusion, oxygen, gas space, mathematical model, tomography

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