The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography

Tracy, Saoirse R.; Roberts, Jeremy A.; Black, C. R.; McNeill, Ann; Davidson, Roger; Mooney, Sacha J.

doi:10.1093/jxb/erp386

Cited by 173 publications

(122 citation statements)

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“…These include growth on moistened germination paper rolls or pouches, sand rhizotrons, rhizoboxes, in compost followed by washing, soil columns and gelbased systems where phenotypic effects can be imaged using flatbed scanners, digital cameras, lasers, or even x-ray computed tomography (CT) (Hetz et al, 1996;Whiting et al, 2000;Bengough et al, 2004;Fang et al, 2009;French et al, 2009;Gregory et al, 2009;Hammond et al, 2009;Iyer-Pascuzzi et al, 2010;Trachsel et al, 2010;Tracy et al, 2010Tracy et al, , 2011Chapman et al, 2011;Lobet et al, 2011;Lucas et al, 2011). Magnetic resonance imaging (for noninvasive analysis of root structures) and positron emission tomography (for analysis of carbon transport and accumulation) can be combined to study the dynamics of structure-function relationships of roots in real soils in a noninvasive manner .…”

Section: How To Image Root Systems?mentioning

confidence: 99%

“…For plants grown in soil, x-ray CT techniques and magnetic resonance imaging (Heeraman et al, 1997;Nagel et al, 2009;Tracy et al, 2010;Lucas et al, 2011;Zhu et al, 2011) have recently increased our capabilities to visualize root system architecture in situ nondestructively. For example, the x-ray CT technique can be used to study root architectures under varying nutrient, moisture, temperature, and soil density conditions in a physiologically relevant way over time.…”

Section: How To Image Root Systems?mentioning

confidence: 99%

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Analyzing Lateral Root Development: How to Move Forward

et al. 2012

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Roots are important to plants for a wide variety of processes, including nutrient and water uptake, anchoring and mechanical support, storage functions, and as the major interface between the plant and various biotic and abiotic factors in the soil environment. Therefore, understanding the development and architecture of roots holds potential for the manipulation of root traits to improve the productivity and sustainability of agricultural systems and to better understand and manage natural ecosystems. While lateral root development is a traceable process along the primary root and different stages can be found along this longitudinal axis of time and development, root system architecture is complex and difficult to quantify. Here, we comment on assays to describe lateral root phenotypes and propose ways to move forward regarding the description of root system architecture, also considering crops and the environment.Root system architecture is a key determinant of nutrient and water use efficiency and describes, on a macro scale, the organization of the primary root and root-and stemderived branches where they are present in monocots and dicots (Hochholdinger et al., 2004;De Smet et al., 2006;Hochholdinger and Zimmermann, 2008;Pé ret et al., 2009;Coudert et al., 2010

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Section: How To Image Root Systems?mentioning

confidence: 99%

Section: How To Image Root Systems?mentioning

confidence: 99%

Analyzing Lateral Root Development: How to Move Forward

et al. 2012

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“…Predictive techniques provide insight about root systems by extrapolating root information from soil cores and root crowns of field-grown plants (Trachsel et al, 2011) or from plants grown in controlled growth systems including hydroponic, pouch, pot, and plate systems. In situ methods involving rhizotron, magnetic resonance, and computed tomography techniques have also been developed to facilitate nondestructive spatial and temporal investigations into root systems grown in soil (Taylor et al, 1990;Gregory et al, 2003;Tracy et al, 2010); however, the current scale, resolution, throughput, and cost efficiency of these techniques limit their utility. Additionally, simulation and modeling studies that integrate rhizosphere and growth data help form links between predictive techniques and field studies, allowing researchers to strategically predict, evaluate, and target beneficial root traits or genotypes for specific growth environments (Berntson, 1994;Ho et al, 2004;de Dorlodot et al, 2007).…”

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confidence: 99%

Three-Dimensional Root Phenotyping with a Novel Imaging and Software Platform

et al. 2011

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A novel imaging and software platform was developed for the high-throughput phenotyping of three-dimensional root traits during seedling development. To demonstrate the platform's capacity, plants of two rice (Oryza sativa) genotypes, Azucena and IR64, were grown in a transparent gellan gum system and imaged daily for 10 d. Rotational image sequences consisting of 40 two-dimensional images were captured using an optically corrected digital imaging system. Three-dimensional root reconstructions were generated and analyzed using a custom-designed software, RootReader3D. Using the automated and interactive capabilities of RootReader3D, five rice root types were classified and 27 phenotypic root traits were measured to characterize these two genotypes. Where possible, measurements from the three-dimensional platform were validated and were highly correlated with conventional two-dimensional measurements. When comparing gellan gum-grown plants with those grown under hydroponic and sand culture, significant differences were detected in morphological root traits (P , 0.05). This highly flexible platform provides the capacity to measure root traits with a high degree of spatial and temporal resolution and will facilitate novel investigations into the development of entire root systems or selected components of root systems. In combination with the extensive genetic resources that are now available, this platform will be a powerful resource to further explore the molecular and genetic determinants of root system architecture.

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“…Imaging techniques for the visualization of soilgrown root systems in two and three dimensions include x-ray computed tomography (Heeraman et al, 1997;Tracy et al, 2010;Mooney et al, 2012), neutron radiography (NR; Oswald et al, 2008), and magnetic resonance imaging (Pohlmeier et al, 2008). NR is one of the most suitable techniques to investigate roots grown in soil, because it allows a high throughput, provides a strong contrast between roots and soil, and therefore requires little effort for image processing.…”

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confidence: 99%

Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

et al. 2013

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Root system traits are important in view of current challenges such as sustainable crop production with reduced fertilizer input or in resource-limited environments. We present a novel approach for recovering root architectural parameters based on imageanalysis techniques. It is based on a graph representation of the segmented and skeletonized image of the root system, where individual roots are tracked in a fully automated way. Using a dynamic root architecture model for deciding whether a specific path in the graph is likely to represent a root helps to distinguish root overlaps from branches and favors the analysis of root development over a sequence of images. After the root tracking step, global traits such as topological characteristics as well as root architectural parameters are computed. Analysis of neutron radiographic root system images of lupine (Lupinus albus) grown in mesocosms filled with sandy soil results in a set of root architectural parameters. They are used to simulate the dynamic development of the root system and to compute the corresponding root length densities in the mesocosm. The graph representation of the root system provides global information about connectivity inside the graph. The underlying root growth model helps to determine which path inside the graph is most likely for a given root. This facilitates the systematic investigation of root architectural traits, in particular with respect to the parameterization of dynamic root architecture models.

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The X-factor: visualizing undisturbed root architecture in soils using X-ray computed tomography

Cited by 173 publications

References 8 publications

Analyzing Lateral Root Development: How to Move Forward

Analyzing Lateral Root Development: How to Move Forward

Three-Dimensional Root Phenotyping with a Novel Imaging and Software Platform

Recovering Root System Traits Using Image Analysis Exemplified by Two-Dimensional Neutron Radiography Images of Lupine

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