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      High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

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          Abstract

          Background

          X-ray computed tomography (CT) allows us to visualize root system architecture (RSA) beneath the soil, non-destructively and in a three-dimensional (3-D) form. However, CT scanning, reconstruction processes, and root isolation from X-ray CT volumes, take considerable time. For genetic analyses, such as quantitative trait locus mapping, which require a large population size, a high-throughput RSA visualization method is required.

          Results

          We have developed a high-throughput process flow for the 3-D visualization of rice ( Oryza sativa) RSA (consisting of radicle and crown roots), using X-ray CT. The process flow includes use of a uniform particle size, calcined clay to reduce the possibility of visualizing non-root segments, use of a higher tube voltage and current in the X-ray CT scanning to increase root-to-soil contrast, and use of a 3-D median filter and edge detection algorithm to isolate root segments. Using high-performance computing technology, this analysis flow requires only 10 min (33 s, if a rough image is acceptable) for CT scanning and reconstruction, and 2 min for image processing, to visualize rice RSA. This reduced time allowed us to conduct the genetic analysis associated with 3-D RSA phenotyping. In 2-week-old seedlings, 85% and 100% of radicle and crown roots were detected, when 16 cm and 20 cm diameter pots were used, respectively. The X-ray dose per scan was estimated at < 0.09 Gy, which did not impede rice growth. Using the developed process flow, we were able to follow daily RSA development, i.e., 4-D RSA development, of an upland rice variety, over 3 weeks.

          Conclusions

          We developed a high-throughput process flow for 3-D rice RSA visualization by X-ray CT. The X-ray dose assay on plant growth has shown that this methodology could be applicable for 4-D RSA phenotyping. We named the RSA visualization method ‘RSAvis3D’ and are confident that it represents a potentially efficient application for 3-D RSA phenotyping of various plant species.

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          Most cited references46

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          Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions.

          The genetic improvement of drought resistance is essential for stable and adequate crop production in drought-prone areas. Here we demonstrate that alteration of root system architecture improves drought avoidance through the cloning and characterization of DEEPER ROOTING 1 (DRO1), a rice quantitative trait locus controlling root growth angle. DRO1 is negatively regulated by auxin and is involved in cell elongation in the root tip that causes asymmetric root growth and downward bending of the root in response to gravity. Higher expression of DRO1 increases the root growth angle, whereby roots grow in a more downward direction. Introducing DRO1 into a shallow-rooting rice cultivar by backcrossing enabled the resulting line to avoid drought by increasing deep rooting, which maintained high yield performance under drought conditions relative to the recipient cultivar. Our experiments suggest that control of root system architecture will contribute to drought avoidance in crops.
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            Root Architecture and Plant Productivity.

            J. Lynch (1995)
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              Plasticity of the Arabidopsis root system under nutrient deficiencies.

              Plant roots show a particularly high variation in their morphological response to different nutrient deficiencies. Although such changes often determine the nutrient efficiency or stress tolerance of plants, it is surprising that a comprehensive and comparative analysis of root morphological responses to different nutrient deficiencies has not yet been conducted. Since one reason for this is an inherent difficulty in obtaining nutrient-deficient conditions in agar culture, we first identified conditions appropriate for producing nutrient-deficient plants on agar plates. Based on a careful selection of agar specifically for each nutrient being considered, we grew Arabidopsis (Arabidopsis thaliana) plants at four levels of deficiency for 12 nutrients and quantified seven root traits. In combination with measurements of biomass and elemental concentrations, we observed that the nutritional status and type of nutrient determined the extent and type of changes in root system architecture (RSA). The independent regulation of individual root traits further pointed to a differential sensitivity of root tissues to nutrient limitations. To capture the variation in RSA under different nutrient supplies, we used principal component analysis and developed a root plasticity chart representing the overall modulations in RSA under a given treatment. This systematic comparison of RSA responses to nutrient deficiencies provides a comprehensive view of the overall changes in root plasticity induced by the deficiency of single nutrients and provides a solid basis for the identification of nutrient-sensitive steps in the root developmental program.
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                Author and article information

                Contributors
                yuga@affrc.go.jp
                Journal
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                1746-4811
                11 May 2020
                11 May 2020
                2020
                : 16
                : 66
                Affiliations
                [1 ]GRID grid.416835.d, ISNI 0000 0001 2222 0432, Institute of Crop Science, , National Agriculture and Food Research Organization, ; Tsukuba, Ibaraki 305-8518 Japan
                [2 ]GRID grid.410858.0, ISNI 0000 0000 9824 2470, Kazusa DNA Research Institute, ; Kisarazu, Chiba 292-0818 Japan
                Author information
                http://orcid.org/0000-0003-4006-954X
                Article
                612
                10.1186/s13007-020-00612-6
                7216661
                32426023
                52846d65-b0e4-4dc9-be7d-62b1f993dec5
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 27 November 2019
                : 5 May 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001695, Japan Science and Technology Corporation;
                Award ID: JPMJCR17O1
                Award Recipient :
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2020

                Plant science & Botany
                image processing,oryza sativa,plant root,root plasticity,rsavis3d,x-ray ct
                Plant science & Botany
                image processing, oryza sativa, plant root, root plasticity, rsavis3d, x-ray ct

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