Advances in the acquisition and analysis of CT scan data to isolate a crop root system from the soil medium and quantify root system complexity in 3-D space

Lontoc-Roy, Melinda; Dutilleul, Pierre; Prasher, Shiv O.; Han, Liwen; Brouillet, Thomas; Smith, Donald L.

doi:10.1016/j.geoderma.2006.08.025

Cited by 88 publications

(65 citation statements)

References 23 publications

(23 reference statements)

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“…In the present study, for simplicity, homogeneous sand was used as the test soil. This allowed a clear differentiation of roots from sand in CT scanning as emphasized by Lontoc-Roy et al (2006). Natural soils, with a more complex structure, can be used in future studies using some modifications of the principles described in the current study and other previous studies ) Taina et al, 2008;Choat et al, 2015).…”

Section: Discussionmentioning

confidence: 84%

“…These voxels were defined to different classes reflecting the scanned specimen components, and building a single model expected from materials of X-ray attenuation data. This approach was conscious to noise and required clear distinction between the grayscale values of the object and its background values ) Pierret et al, 1999;Lontoc-Roy et al, 2006;Kaestner et al, 2006 andPerret et al, 2007). Although the thresholding techniques alone scarcely supplies sufficient accurate results, it is often combined with additional operations.…”

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confidence: 99%

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A Simple Method to Measure Key Parameters of Soil-root Structure Using Medical X-ray Tomography Scanning Technique

2017

Egypt.J. Soil Sci.

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ROOTS have an extreme impact on soil properties and parameters are essential toward successful crop management. The study aims at modifying simple and quick method to identify key parameters of root structure by using medical X-ray CT )X-ray computed tomography) scanning technique and assesses its potentials.The results reveal that the modified simple procedures made it possible to isolate the root from the soil and partially overcome the problem of partial volume effect, and the main taproot was shown located at 0 to 30 mm depth. This procedure presented appropriate technique for segmenting large amounts of data. The modified method reduced the duration of the experiment and the risk of sample disturbance compared with the conventional methods to derive the architecture and the functional imaging. Results of plant growth parameters were closely related to the morphological parameters measured using the medical X-ray CT techniques.This approach enabledobservingroot growth manner and how individual roots overcome obstacles on their way. The technique modification shows great potential to provide new fundamental insights into soil-plant interactions and increase understanding of soil plant relationship. 13

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Section: Discussionmentioning

confidence: 84%

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confidence: 99%

A Simple Method to Measure Key Parameters of Soil-root Structure Using Medical X-ray Tomography Scanning Technique

2017

Egypt.J. Soil Sci.

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“…The method does not guarantee connectivity and outlier voxels can easily be assigned to incorrect components. Seeking to advance imaging and analysis procedures, Lontoc-Roy et al [16] presented methods and results obtained using X-ray CT for soil-root studies. Roots were segmented from the images by visually choosing lower and upper threshold values.…”

Section: Related Workmentioning

confidence: 99%

“…Analogous to the method presented by Lontoc-Roy et al [16], a conservative threshold was employed within a threedimensional region growing algorithm to recover the primary tree of the airway structure, but typically missed fine, smaller diameter segments. To improve performance on small airways, the image was scaled by a factor of 2 and enhanced using a top-hat transform [26].…”

Section: Related Workmentioning

confidence: 99%

Visual tracking for the recovery of multiple interacting plant root systems from X-ray $$\upmu $$ μ CT images

Mairhofer

Johnson

Sturrock

et al. 2015

Machine Vision and Applications

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We propose a visual object tracking framework for the extraction of multiple interacting plant root systems from three-dimensional X-ray micro computed tomography images of plants grown in soil. Our method is based on a level set framework guided by a greyscale intensity distribution model to identify object boundaries in image cross-sections. Root objects are followed through the data volume, while updating the tracker's appearance models to adapt to changing intensity values. In the presence of multiple root systems, multiple trackers can be used, but need to distinguish target objects from one another in order to correctly associate roots with their originating plants. Since root objects are expected to exhibit similar greyscale intensity distributions, shape information is used to constrain the evolving level set interfaces in order to lock trackers to their correct targets. The proposed method is tested on root systems of wheat plants grown in soil.

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“…For instance, Pierret et al (1999) and Kaestner et al (2006) both used different morphological operations for postprocessing to determine whether remaining voxels should belong to the final outcome or not. Lontoc-Roy et al (2006) and Perret et al (2007), in turn, performed an explicit connectivity check to identify voxels that have fallen within the threshold limits but are not part of root system. The resulting methods operate in a bottom-up fashion, starting with the raw data and moving toward root descriptions through a sequence of operations, each applied to the entire sample.…”

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confidence: 99%

RooTrak: Automated Recovery of Three-Dimensional Plant Root Architecture in Soil from X-Ray Microcomputed Tomography Images Using Visual Tracking

et al. 2011

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X-ray microcomputed tomography (mCT) is an invaluable tool for visualizing plant root systems within their natural soil environment noninvasively. However, variations in the x-ray attenuation values of root material and the overlap in attenuation values between roots and soil caused by water and organic materials represent major challenges to data recovery. We report the development of automatic root segmentation methods and software that view mCT data as a sequence of images through which root objects appear to move as the x-y cross sections are traversed along the z axis of the image stack. Previous approaches have employed significant levels of user interaction and/or fixed criteria to distinguish root and nonroot material. RooTrak exploits multiple, local models of root appearance, each built while tracking a specific segment, to identify new root material. It requires minimal user interaction and is able to adapt to changing root density estimates. The model-guided search for root material arising from the adoption of a visual-tracking framework makes RooTrak less sensitive to the natural ambiguity of x-ray attenuation data. We demonstrate the utility of RooTrak using mCT scans of maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum) grown in a range of contrasting soil textures. Our results demonstrate that RooTrak can successfully extract a range of root architectures from the surrounding soil and promises to facilitate future root phenotyping efforts.

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Advances in the acquisition and analysis of CT scan data to isolate a crop root system from the soil medium and quantify root system complexity in 3-D space

Cited by 88 publications

References 23 publications

A Simple Method to Measure Key Parameters of Soil-root Structure Using Medical X-ray Tomography Scanning Technique

A Simple Method to Measure Key Parameters of Soil-root Structure Using Medical X-ray Tomography Scanning Technique

Visual tracking for the recovery of multiple interacting plant root systems from X-ray $$\upmu $$ μ CT images

RooTrak: Automated Recovery of Three-Dimensional Plant Root Architecture in Soil from X-Ray Microcomputed Tomography Images Using Visual Tracking

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