A methodology for obtaining visual and quantitative root structure information from X-ray computed tomography data acquired in-soil is presented.
Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and crop management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving plants. X-ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. We aimed to develop a costless and efficient tool that approximates the surface and volume of the root regardless of its shape from three-dimensional (3D) tomography data. The root structure of a Prairie dropseed (Sporobolus heterolepis) specimen was imaged using XCT. The root was reconstructed, and the primary root structure was extracted from the data using a combination of licensed and open-source software. An isosurface polygonal mesh was then created for ease of analysis. We have developed the standalone application imeshJ, generated in MATLAB1, to calculate root volume and surface area from the mesh. The outputs of imeshJ are surface area (in mm2) and the volume (in mm3). The process, utilizing a unique combination of tools from imaging to quantitative root analysis, is described. A combination of XCT and open-source software proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information from the 3D data. This methodology of processing 3D data should be applicable to other material/sample systems where there is connectivity between components of similar X-ray attenuation and difficulties arise with segmentation.
Roots, as part of the rhizosphere2-5, represent an "invisible" part of plant biology since soil makes it difficult to image roots non-invasively 6, 7. However, studying root growth and interaction within the soil environment is critical to understanding root/plant growth and nutrient cycling, which in turn affect forestation, food security, and climate. X-ray computed tomography (XCT) has proven to be a valuable tool for noninvasive imaging of plant root samples in their local environments 8. In order to measure root development and dimensional changes under different conditions, and be able to compare data from different datasets/specimens, one needs to extract quantitative information from the tomography data. Segmentation of the root data from that of the surrounding soil, that is, the isolation of the root image from everything else around it (including, for example, a neighboring plant) is a critical step before accurate size analysis can be done. However, a simple thresholding approach is often unfeasible for root data. The challenges associated with imaging plant roots in soil include variations in the X-ray attenuation properties of the root material, and the overlap in attenuation values between root and soil caused by water and organic matter. These issues have been superbly addressed recently by Mairhofer et al. in their visual tracking tool RooTrak 7, 9. The next step after a successful segmentation is the accurate determination of root volume and surface area. The volume may be estimated by counting the number of voxels and multiplying by the voxels' size cubed as shown before7. For a more accurate determination of root surface area and volume, the isosurface of the segmented root system can be represented by a mesh of triangles, using an algorithm known as Marching Cubes 10. The open-source ImageJ11 can be employed to approximate the root volume based on the Marching Cubes algorithm. To the best of our knowledge, only a limited number of open-source software dedicated to calculating tomography-based volume/surface data for root specimens in the centimeter range and above is currently available 12. One open-source software we looked at13 focuses on root growth and is aimed at cellular features enabling quantitative volume analysis at single-cell resolution. Some open-source software dedicated to whole root systems14 is excellent for small-diameter tubular root systems based on the approximation that their shape is actually tubular. However, some work with 2D images and are unable to handle 3D stacks14. Furthermore, the tubular shape approximation may not be valid when root systems with rough surfaces and non-uniform shapes, such as those of trees, are studied. Another approach15 uses two-dimensional (2D) rotational image sequences innovatively circumventing the need for a costly CT scanner. It measures, records, and displays root system lengths. The software we have tested from those only available commercially16-18; one does not appear to be able to handle 3D image stacks16, the second is a leaf area and root length measurement tool17, while the third is based on color analysis18. Based on this survey, we suggest that a costless option that approximates the surface and volume of the root regardless of its shape from 3D tomography data is desirable.
Building on the freely available RooTrak and ImageJ, we have developed a program, named imeshJ (see Supplemental Code File) which processes an isosurface mesh (surface stereolithography file) generated from segmented root data, and calculates the volume and surface area of the root by doing simple geometrical calculations on the mesh triangle index data. Here we report a method that combines the use of XCT imaging, data reconstruction and visualization (software CT Pro 3D and VG Studio), segmentation of the root of the specimen from the soil in the 3D data (open-source software ImageJ and RooTrak), and extraction of the surface and volume information from a triangular mesh (ImageJ and the computer code imeshJ).
A combination of X-ray computed tomography and several open-source programs proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information (surface area and volume) from the 3D data. Our ability to visualize and measure features is always limited by scan resolution, as well as by limitations of the RooTrak software. However, scan resolution was sufficient to capture the majority of the features of the sample in this study, and RooTrak was able to suc…
The authors have nothing to disclose.
This work was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.
X-Tek/Metris XTH 320/225 kV | Nikon Metrology | n/a | X-ray tomography scanner |
Inspect X | Nikon Metrology | n/a | Instrument control software |
CT Pro 3D | Nikon Metrology | n/a | Reconstruction software, version XT 2.2 |
VG Studio MAX | Visual Graphics GmbH | n/a | Visualization software for 3D volumes, version 2.1.5 |
ImageJ | Open-source | n/a | Image processing and analysis software, version 1.6 |
RooTrak | Open-source | n/a | Root segmentation software, version 0.3.1-b1 beta |
imeshJ | EMSL | n/a | MATLAB script developed by the authors |
Prairie dropseed grass sample | n/a | n/a | Sample obtained from ground in residential area |