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

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          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 (S mes) 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 S mes for the dicot species whereas barley had the highest porosity and the highest S mes for the grass species. Comparison of porosity and S mes 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 S mes 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 S mes 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.

          Electronic supplementary material

          The online version of this article (10.1186/s13007-018-0367-7) contains supplementary material, which is available to authorized users.

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          Most cited references41

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Yield Trends Are Insufficient to Double Global Crop Production by 2050

            Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops—maize, rice, wheat, and soybean—that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
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              Meeting the global food demand of the future by engineering crop photosynthesis and yield potential.

              Increase in demand for our primary foodstuffs is outstripping increase in yields, an expanding gap that indicates large potential food shortages by mid-century. This comes at a time when yield improvements are slowing or stagnating as the approaches of the Green Revolution reach their biological limits. Photosynthesis, which has been improved little in crops and falls far short of its biological limit, emerges as the key remaining route to increase the genetic yield potential of our major crops. Thus, there is a timely need to accelerate our understanding of the photosynthetic process in crops to allow informed and guided improvements via in-silico-assisted genetic engineering. Potential and emerging approaches to improving crop photosynthetic efficiency are discussed, and the new tools needed to realize these changes are presented.
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                Author and article information

                Contributors
                mathers.andrew@googlemail.com
                c.hepworth@sheffield.ac.uk
                a.baillie@sheffield.ac.uk
                j.sloan@sheffield.ac.uk
                hannah.jones@sheffield.ac.uk
                m.lundgren@lancaster.ac.uk
                a.fleming@sheffield.ac.uk
                sacha.mooney@nottingham.ac.uk
                craig.sturrock@nottingham.ac.uk
                Journal
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                1746-4811
                12 November 2018
                12 November 2018
                2018
                : 14
                : 99
                Affiliations
                [1 ]ISNI 0000 0004 1936 8868, GRID grid.4563.4, Division of Agricultural and Environmental Sciences, School of Biosciences, , University of Nottingham, ; Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD UK
                [2 ]ISNI 0000 0004 1936 9262, GRID grid.11835.3e, Department of Animal and Plant Sciences, , University of Sheffield, ; Western Bank, Sheffield, S10 2TN UK
                [3 ]ISNI 0000 0000 8190 6402, GRID grid.9835.7, Lancaster Environment Centre, , Lancaster University, ; LEC 2 Yellow Zone B43, Lancaster, LA1 4YQ UK
                Article
                367
                10.1186/s13007-018-0367-7
                6231253
                30455724
                e343a18c-fba1-42ee-a358-87d32a6367dd
                © The Author(s) 2018

                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
                : 31 July 2018
                : 3 November 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/N013719/1
                Award ID: BB/J004065/1
                Award Recipient :
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2018

                Plant science & Botany
                x-ray computed tomography (microct),porosity,leaf structure,air channels,gas exchange,photosynthesis

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