Existing and Potential Statistical and Computational Approaches for the Analysis of 3D CT Images of Plant Roots

Xu, Zheng; Valdes, Camilo; Clarke, Jennifer

doi:10.3390/agronomy8050071

Cited by 24 publications

(10 citation statements)

References 69 publications

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“…A completed review of the existing computational approaches for root system tracking by 3D X-ray CT data is done in Xu et al (2018). Some software tools are highlighted but they are not able to automatically compute root traits.…”

Section: Introductionmentioning

confidence: 99%

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4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography

2022

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Currently, plant phenomics is considered the key to reducing the genotype-to-phenotype knowledge gap in plant breeding. In this context, breakthrough imaging technologies have demonstrated high accuracy and reliability. The X-ray computed tomography (CT) technology can noninvasively scan roots in 3D; however, it is urgently required to implement high-throughput phenotyping procedures and analyses to increase the amount of data to measure more complex root phenotypic traits. We have developed a spatial-temporal root architectural modeling software tool based on 4D data from temporal X-ray CT scans. Through a cylinder fitting, we automatically extract significant root architectural traits, distribution, and hierarchy. The open-source software tool is named 4DRoot and implemented in MATLAB. The source code is freely available at https://github.com/TIDOP-USAL/4DRoot. In this research, 3D root scans from the black walnut tree were analyzed, a punctual scan for the spatial study and a weekly time-slot series for the temporal one. 4DRoot provides breeders and root biologists an objective and useful tool to quantify carbon sequestration throw trait extraction. In addition, 4DRoot could help plant breeders to improve plants to meet the food, fuel, and fiber demands in the future, in order to increase crop yield while reducing farming inputs.

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Section: Introductionmentioning

confidence: 99%

“…This modeling approach consists of, first, segmentation into ramifications, and second, fitting cylinders into these ramifications (Xu et al, 2018). The segmentation uses small surface patches to identify bifurcations along the root by computing the local connectivity of a moving region (Raumonen et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography

2022

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“…Allied to rhizotrons are X-ray computed tomography (CT) systems capable of visualising detailed root structures in soil. Industrial micro-CT systems with resolutions of 500 nm or less (Mooney et al, 2012;Xu et al,2018), coupled with automated systems for sample presentation and data processing (Mairhofer et al, 2012), are also a valuable tool for root phenotyping in rhizotrons.…”

Section: Introductionmentioning

confidence: 99%

Wheat Varietal Differences in Below Ground Biomass Revealed by a Semi-Quantitative Estimation of Wheat Root DNA in Soil Samples

Jones¹,

Bentley²,

Smith³

et al. 2019

Preprint

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Root research on field grown crops is hindered by the difficulty of estimating root biomass in soil. Root washing, the current standard method is laborious and expensive. Biochemical methods to quantify root biomass in soil, targeting species-specific DNA, have potential as a more efficient assay. We combined an efficient DNA extraction method, designed specifically to extract DNA from soil, with well-established quantitative PCR methods to estimate the root biomass of twenty-two wheat varieties grown in field trials over two seasons. We also developed an assay for estimating root biomass for black-grass, a common weed of wheat cultivation. Two robust qPCR assays were developed to estimate the quantity of plant root DNA in soil samples, one specific to wheat and barley, and a second specific to black-grass. The DNA qPCR method was comparable, with high correlations, with the results of root washing from soil cores taken from winter wheat field trials. The DNA qPCR assay showed both variety and depth as significant factors in the distribution of root biomass in replicated field trials. The results suggest that these DNA qPCR assays are a useful, high throughput tool for investigating the genetic basis of wheat root biomass distribution in field grown crops, and the impact of black-grass root systems on crop production.

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“…For the research in the 3D architecture of plant roots, some researchers applied laser scanning technology, MRI technology, and X-ray CT technology to the detection of plant roots architecture [13] . Gregory et al performed non-invasive imaging of roots using high-resolution X-ray tomography [14] .…”

Section: Introductionmentioning

confidence: 99%

Centerline extraction based three-dimensional architecture parameter measurement method for plant roots

Yang

Zhou

Chen

et al. 2018

International Journal of Precision Agricultural Aviation

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The detection of architecture was one of the essential questions of plant root phenotyping research. The classical root architecture detection method was carried out by manual measurement. It is not only tedious, but also has a poor reliability, and the roots are damaged easily. This paper described a three-dimensional architecture measurement method based on XCT and centerline extraction method. The method includes the following steps: (1) obtaining the root CT images through the XCT system; (2) obtaining a root three-dimensional model after image segmentation and reconstruction. To solve the problem of model fracture, the quality of the reconstruction model was improved by a series of pre-processing methods; (3) extracting the root's centerline based on the mesh contraction, and the high-quality centerline was obtained after the post-processing methods; (4) calculating the architecture parameters. Different root samples were tested to validate the method for centerline extraction, and the root architecture was calculated by the centerline. The results were compared with the manual measurements, and the mean absolute percentage error of root length and root angle were 1.74% and 4.51, respectively. The entire algorithm runs for less than 30 seconds. The study may provide an effective method for root architecture detection.

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Existing and Potential Statistical and Computational Approaches for the Analysis of 3D CT Images of Plant Roots

Cited by 24 publications

References 69 publications

4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography

4DRoot: Root phenotyping software for temporal 3D scans by X-ray computed tomography

Wheat Varietal Differences in Below Ground Biomass Revealed by a Semi-Quantitative Estimation of Wheat Root DNA in Soil Samples

Centerline extraction based three-dimensional architecture parameter measurement method for plant roots

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