Using X-ray Computed Tomography to explore the role of abscisic acid in moderating the impact of soil compaction on root system architecture

2015 ◽  
Vol 110 ◽  
pp. 11-18 ◽  
Author(s):  
Saoirse R. Tracy ◽  
Colin R. Black ◽  
Jeremy A. Roberts ◽  
Ian C. Dodd ◽  
Sacha J. Mooney
Keyword(s):  
Computed Tomography ◽  
Abscisic Acid ◽  
Root System ◽  
System Architecture ◽  
Soil Compaction ◽  
Root System Architecture ◽  
X Ray ◽  
X Ray Computed ◽  
The Impact

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

2012 ◽  
Vol 110 (2) ◽  
pp. 511-519 ◽  
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

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

2013 ◽  
Vol 370 (1-2) ◽  
pp. 35-45 ◽  
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

scholarly journals X-Ray Computed Tomography Reveals the Response of Root System Architecture to Soil Texture

2016 ◽  
Vol 171 (3) ◽  
pp. 2028-2040 ◽  
Author(s):  
Eric D. Rogers ◽  
Daria Monaenkova ◽  
Medhavinee Mijar ◽  
Apoorva Nori ◽  
Daniel I. Goldman ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
Soil Texture ◽  
System Architecture ◽  
Root System Architecture ◽  
X Ray ◽  
X Ray Computed

scholarly journals High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography

Plant Methods ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Shota Teramoto ◽  
Satoko Takayasu ◽  
Yuka Kitomi ◽  
Yumiko Arai-Sanoh ◽  
Takanari Tanabata ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
High Throughput ◽  
System Architecture ◽  
Three Dimensional ◽  
Root System Architecture ◽  
X Ray ◽  
X Ray Computed

In Situ Visualization and Quantification of Three-Dimensional Root System Architecture and Growth Using X-Ray Computed Tomography

2014 ◽  
Vol 13 (8) ◽  
pp. vzj2014.03.0024 ◽  
Author(s):  
Nicolai Koebernick ◽  
Ulrich Weller ◽  
Katrin Huber ◽  
Steffen Schlüter ◽  
Hans-Jörg Vogel ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
System Architecture ◽  
Three Dimensional ◽  
Root System Architecture ◽  
X Ray ◽  
In Situ Visualization ◽  
X Ray Computed

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

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.

scholarly journals Understanding the Intricate Web of Phytohormone Signalling in Modulating Root System Architecture

2021 ◽  
Vol 22 (11) ◽  
pp. 5508
Author(s):  
Manvi Sharma ◽  
Dhriti Singh ◽  
Harshita B. Saksena ◽  
Mohan Sharma ◽  
Archna Tiwari ◽  
...  
Keyword(s):  
Root System ◽  
Root Development ◽  
System Architecture ◽  
Soil Compaction ◽  
Lateral Roots ◽  
Root System Architecture ◽  
Physical Factors ◽  
Future Perspectives ◽  
External Cues

Root system architecture (RSA) is an important developmental and agronomic trait that is regulated by various physical factors such as nutrients, water, microbes, gravity, and soil compaction as well as hormone-mediated pathways. Phytohormones act as internal mediators between soil and RSA to influence various events of root development, starting from organogenesis to the formation of higher order lateral roots (LRs) through diverse mechanisms. Apart from interaction with the external cues, root development also relies on the complex web of interaction among phytohormones to exhibit synergistic or antagonistic effects to improve crop performance. However, there are considerable gaps in understanding the interaction of these hormonal networks during various aspects of root development. In this review, we elucidate the role of different hormones to modulate a common phenotypic output, such as RSA in Arabidopsis and crop plants, and discuss future perspectives to channel vast information on root development to modulate RSA components.

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

Microscopy ◽  
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.

scholarly journals An improved method for the segmentation of roots from X-Ray computed tomography 3D images: Rootine v.2

2020 ◽  
Author(s):  
Maxime Phalempin ◽  
Eva Lippold ◽  
Doris Vetterlein ◽  
Steffen Schlueter
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
Root System Architecture ◽  
Root Diameter ◽  
Image Resolution ◽  
Absolute Difference ◽  
Improved Method ◽  
3D Images ◽  
X Ray ◽  
X Ray Computed

<p>X-ray computed tomography (CT) is acknowledged as a powerful tool for the study of root system architecture (RSA) of plants grown in soil. The study of the root system properties is however only possible after performing root segmentation, i.e. the binarization of all root voxels. Root segmentation is often regarded as a tedious and difficult task as its success depends on several factors such as the image resolution, the signal to noise during image acquisition and the gray value contrast between the roots and all other surrounding features. Here, we present an improved method for the segmentation of roots from X-Ray computed tomography 3D images. The algorithm Rootine (Gao et al. 2019) does not detect roots by their gray values but by their characteristic tubular shape. This algorithm was further developed in order to improve the root recovery rate and to reduce the number of parameters involved during the segmentation process. This was achieved by adding two key steps: (1) an absolute difference transform and (2) an automatic calculation of the parameters used during the Gaussian smoothing. The first step allows for targeting specific features based on a gray value criteria contained within a user-defined gray value range in order to better distinguish roots from pores whereas the second step allows for targeting root segments of specific diameters. On the benchmark dataset of Gao et al. 2019, the newly called “Rootine v.2” was able to recover 34 % more roots as compared to its preceding version. Moreover, the number of parameters was reduced from 10 down to 5 which allows for a faster calibration and an overall better usability of the algorithm. The presented method also allows for a more reliable estimation of root diameter derived from X-Ray CT images. This work was carried out in the framework of the priority programme 2089 “Rhizosphere spatiotemporal organization - a key to rhizosphere functions” funded by DFG (project number 403640293).</p>

Sign in / Sign up

Export Citation Format

Share Document