Complementary Phenotyping of Maize Root System Architecture by Root Pulling Force and X-Ray Imaging

The root system is critical for the survival of nearly all land plants and a key target for improving abiotic stress tolerance, nutrient accumulation, and yield in crop species. Although many methods of root phenotyping exist, within field studies, one of the most popular methods is the extraction and measurement of the upper portion of the root system, known as the root crown, followed by trait quantification based on manual measurements or 2D imaging. However, 2D techniques are inherently limited by the information available from single points of view. Here, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample. This approach improves estimates of the genetic contribution to root system architecture and is refined enough to detect various changes in global root system architecture over developmental time as well as more subtle changes in root distributions as a result of environmental differences. We demonstrate that root pulling force, a high-throughput method of root extraction that provides an estimate of root mass, is associated with multiple 3D traits from our pipeline. Our combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts or scaled up as a stand-alone approach in large genetic studies of root system architecture.

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Complementary Phenotyping of Maize Root Architecture by Root Pulling Force and X-Ray Computed Tomography

10.1101/2021.03.03.433776 ◽

2021 ◽

Author(s):

Mon-Ray Shao ◽

Ni Jiang ◽

Mao Li ◽

Anne Howard ◽

Kevin Lehner ◽

...

Keyword(s):

Computed Tomography ◽

Root System ◽

System Architecture ◽

Abiotic Stress Tolerance ◽

Root System Architecture ◽

Maize Root ◽

Crop Species ◽

X Ray ◽

X Ray Computed ◽

Pulling Force

ABSTRACTThe root system is critical for the survival of nearly all land plants and a key target for improving abiotic stress tolerance, nutrient accumulation, and yield in crop species. Although many methods of root phenotyping exist, within field studies one of the most popular methods is the extraction and measurement of the upper portion of the root system, known as the root crown, followed by trait quantification based on manual measurements or 2D imaging. However, 2D techniques are inherently limited by the information available from single points of view. Here, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample. This approach improves estimates of the genetic contribution to root system architecture, and is refined enough to detect various changes in global root system architecture over developmental time as well as more subtle changes in root distributions as a result of environmental differences. We demonstrate that root pulling force, a high-throughput method of root extraction that provides an estimate of root biomass, is associated with multiple 3D traits from our pipeline. Our combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts, or scaled up as a stand-alone approach in large genetic studies of root system architecture.

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TopoRoot: A method for computing hierarchy and fine-grained traits of maize roots from X-ray CT images

10.1101/2021.08.24.457522 ◽

2021 ◽

Author(s):

Dan Zeng ◽

Mao Li ◽

Ni Jiang ◽

Yiwen Ju ◽

Hannah Schreiber ◽

...

Keyword(s):

Root System ◽

System Architecture ◽

State Of The Art ◽

Root System Architecture ◽

Ct Images ◽

Maize Root ◽

Root Number ◽

X Ray ◽

Fine Grained ◽

Maize Roots

Background: 3D imaging, such as X-ray CT and MRI, has been widely deployed to study plant root structures. Many computational tools exist to extract coarse-grained features from 3D root images, such as total volume, root number and total root length. However, methods that can accurately and efficiently compute fine-grained root traits, such as root number and geometry at each hierarchy level, are still lacking. These traits would allow biologists to gain deeper insights into the root system architecture (RSA). Results: We present TopoRoot, a high-throughput computational method that computes fine-grained architectural traits from 3D X-ray CT images of field-excavated maize root crowns. These traits include the number, length, thickness, angle, tortuosity, and number of children for the roots at each level of the hierarchy. TopoRoot combines state-of-the-art algorithms in computer graphics, such as topological simplification and geometric skeletonization, with customized heuristics for robustly obtaining the branching structure and hierarchical information. TopoRoot is validated on both real and simulated root images, and in both cases it was shown to improve the accuracy of traits over existing methods. We also demonstrate TopoRoot in differentiating a maize root mutant from its wild type segregant using fine-grained traits. TopoRoot runs within a few minutes on a desktop workstation for volumes at the resolution range of 400^3, without need for human intervention. Conclusions: TopoRoot improves the state-of-the-art methods in obtaining more accurate and comprehensive fine-grained traits of maize roots from 3D CT images. The automation and efficiency makes TopoRoot suitable for batch processing on a large number of root images. Our method is thus useful for phenomic studies aimed at finding the genetic basis behind root system architecture and the subsequent development of more productive crops.

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Visualization of Arabidopsis Root System Architecture in 3D by Refraction-Contrast X-Ray Micro-Computed Tomography

Microscopy ◽

10.1093/jmicro/dfab027 ◽

2021 ◽

Author(s):

Tomofumi Kurogane ◽

Daisuke Tamaoki ◽

Sachiko Yano ◽

Fumiaki Tanigaki ◽

Toru Shimazu ◽

...

Keyword(s):

Computed Tomography ◽

Root System ◽

System Architecture ◽

Root Systems ◽

Root System Architecture ◽

Field Of View ◽

Imaging Method ◽

Wide Field ◽

Crop Species ◽

X Ray

Abstract Plant roots change their morphological traits in order to adapt themselves to different environmental conditions, resulting in alteration of the root system architecture. To understand this mechanism, it is essential to visualize morphology of the entire root system. To reveal effects of long-term alteration of gravity environment on root system development, we have performed an experiment in the International Space Station using Arabidopsis plants and obtained dried root systems grown in rockwool slabs. X-ray computed tomography (CT) technique using industrial X-ray scanners has been introduced to visualize root system architecture of crop species grown in soil in 3D non-invasively. In the case of the present study, however, root system of Arabidopsis is composed of finer roots compared with typical crop plants and rockwool is also composed of fibers having similar dimension to that of the roots. A higher spatial resolution imaging method is required for distinguishing roots from rockwool. Therefore, in the present study, we tested refraction-contrast X-ray micro-CT using coherent X-ray optics available at the beamline of the synchrotron radiation facility SPring-8 for bio-imaging. We have found that wide field of view but with low resolution obtained at the experimental Hutch 3 of this beamline provided an overview map of the root systems, while narrow field of view but with high resolution obtained at the experimental Hutch 1 provided extended architecture of the secondary roots, by clear distinction between roots and individual rockwool fibers, resulting in successful tracing of these roots from their basal regions.

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Quantifying the impact of soil compaction on root system architecture in tomato (Solanum lycopersicum) by X-ray micro-computed tomography

Annals of Botany ◽

10.1093/aob/mcs031 ◽

2012 ◽

Vol 110 (2) ◽

pp. 511-519 ◽

Cited By ~ 86

Author(s):

Saoirse R. Tracy ◽

Colin R. Black ◽

Jeremy A. Roberts ◽

Craig Sturrock ◽

Stefan Mairhofer ◽

...

Keyword(s):

Computed Tomography ◽

Root System ◽

Solanum Lycopersicum ◽

System Architecture ◽

Soil Compaction ◽

Root System Architecture ◽

Micro Computed Tomography ◽

X Ray ◽

The Impact

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<i>RootRobot: A Field-based Platform for Maize Root System Architecture Phenotyping</i>

10.13031/aim.201900806 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xiaomeng Shi ◽

Daeun Choi ◽

Paul Heinz Heinemann ◽

Molly Hanlon ◽

Jonathan Lynch

Keyword(s):

Root System ◽

System Architecture ◽

Root System Architecture ◽

Maize Root

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Modelling Root System Architecture: Experimental Data on Maize Root System Geometry

Plant Roots and their Environment - Developments in Agricultural and Managed Forest Ecology ◽

10.1016/b978-0-444-89104-4.50084-0 ◽

1991 ◽

pp. 620-627 ◽

Cited By ~ 1

Author(s):

S. PELLERIN ◽

F. TARDIEU ◽

F. TRICOT

Keyword(s):

Experimental Data ◽

Root System ◽

System Architecture ◽

Root System Architecture ◽

Maize Root ◽

System Geometry

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Quantifying the effect of soil moisture content on segmenting root system architecture in X-ray computed tomography images

Plant and Soil ◽

10.1007/s11104-013-1596-1 ◽

2013 ◽

Vol 370 (1-2) ◽

pp. 35-45 ◽

Cited By ~ 31

Author(s):

Susan Zappala ◽

Stefan Mairhofer ◽

Saoirse Tracy ◽

Craig J. Sturrock ◽

Malcolm Bennett ◽

...

Keyword(s):

Computed Tomography ◽

Soil Moisture ◽

Moisture Content ◽

Root System ◽

System Architecture ◽

Soil Moisture Content ◽

Root System Architecture ◽

X Ray ◽

Computed Tomography Images ◽

X Ray Computed

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Signaling pathways underlying nitrogen-dependent changes in root system architecture: from model to crop species

Journal of Experimental Botany ◽

10.1093/jxb/eraa033 ◽

2020 ◽

Vol 71 (15) ◽

pp. 4393-4404 ◽

Cited By ~ 13

Author(s):

Zhongtao Jia ◽

Nicolaus von Wirén

Keyword(s):

Nutritional Status ◽

Root System ◽

System Architecture ◽

Molecular Mechanisms ◽

N Uptake ◽

Root System Architecture ◽

Water Soluble ◽

Organic N ◽

Limiting Factor ◽

Crop Species

Abstract Among all essential mineral elements, nitrogen (N) is required in the largest amounts and thus is often a limiting factor for plant growth. N is taken up by plant roots in the form of water-soluble nitrate, ammonium, and, depending on abundance, low-molecular weight organic N. In soils, the availability and composition of these N forms can vary over space and time, which exposes roots to various local N signals that regulate root system architecture in combination with systemic signals reflecting the N nutritional status of the shoot. Uncovering the molecular mechanisms underlying N-dependent signaling provides great potential to optimize root system architecture for the sake of higher N uptake efficiency in crop breeding. In this review, we summarize prominent signaling mechanisms and their underlying molecular players that derive from external N forms or the internal N nutritional status and modulate root development including root hair formation and gravitropism. We also compare the current state of knowledge of these pathways between Arabidopsis and graminaceous plant species.

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