Journal Article FZJ-2019-04150

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Combination of Magnetic Resonance Imaging and Neutron Computed Tomography for Three-Dimensional Rhizosphere Imaging

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2019
GeoScienceWorld Alexandria, Va.

Vadose zone journal 18(1), () [10.2136/vzj2018.09.0166]

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Abstract: In situ investigations of the rhizosphere require high-resolution imaging techniques, which allow a look into the optically opaque soil compartment. We present the novel combination of magnetic resonance imaging (MRI) and neutron computed tomography (NCT) to achieve synergistic information such as water mobility in terms of three-dimensional (3D) relaxation time maps and total water content maps. Besides a stationary MRI scanner for relaxation time mapping, we used a transportable MRI system on site in the NCT facility to capture rhizosphere properties before desiccation and after subsequent rewetting. First, we addressed two questions using water-filled test capillaries between 0.1 and 5 mm: which root diameters can still be detected by both methods, and to what extent are defined interfaces blurred by these imaging techniques? Going to real root system architecture, we demonstrated the sensitivity of the transportable MRI device by co-registration with NCT and additional validation using X-ray computed tomography. Under saturated conditions, we observed for the rhizosphere in situ a zone with shorter T1 relaxation time across a distance of about 1 mm that was not caused by reduced water content, as proven by successive NCT measurements. We conclude that the effective pore size in the pore network had changed, induced by a gel phase. After rewetting, NCT images showed a dry zone persisting while the MRI intensity inside the root increased considerably, indicating water uptake from the surrounding bulk soil through the still hydrophobic rhizosphere. Overall, combining NCT and MRI allows a more detailed analysis of the rhizosphere’s functioning.

Classification:

Contributing Institute(s):
  1. Agrosphäre (IBG-3)
Research Program(s):
  1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2019
Database coverage:
Medline ; Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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 Record created 2019-08-09, last modified 2021-01-30