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Title: What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere. X-ray Computed Tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and in-house developed code was used to non-invasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure, and extract quantitative information from the 3D data, respectively. Based on the explicitly-resolved root structure, pore-scale computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. Furthermore, the coupled imaging-modeling approach demonstrates a realistic platform to investigate rhizosphere flow processes and would be feasible to provide useful information linked to upscaled models.
Authors:
 [1] ;  [2] ;  [3] ;  [2]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Environmental Molecular Sciences Lab., Richland, WA (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Southern Univ. of Science and Technology, Guangzhou (China)
Publication Date:
Report Number(s):
PNNL-SA-124115
Journal ID: ISSN 2452-2198; PII: S2452219817300393
Grant/Contract Number:
AC05-76RL01830
Type:
Accepted Manuscript
Journal Name:
Rhizosphere
Additional Journal Information:
Journal Volume: 3; Journal Issue: P2; Journal ID: ISSN 2452-2198
Publisher:
Elsevier
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING; root model; X-ray Computed Tomography; pore-scale modeling; root water uptake; rhizosphere
OSTI Identifier:
1364399

Yang, Xiaofan, Varga, Tamas, Liu, Chongxuan, and Scheibe, Timothy D. What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system. United States: N. p., Web. doi:10.1016/J.RHISPH.2017.04.017.
Yang, Xiaofan, Varga, Tamas, Liu, Chongxuan, & Scheibe, Timothy D. What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system. United States. doi:10.1016/J.RHISPH.2017.04.017.
Yang, Xiaofan, Varga, Tamas, Liu, Chongxuan, and Scheibe, Timothy D. 2017. "What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system". United States. doi:10.1016/J.RHISPH.2017.04.017. https://www.osti.gov/servlets/purl/1364399.
@article{osti_1364399,
title = {What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system},
author = {Yang, Xiaofan and Varga, Tamas and Liu, Chongxuan and Scheibe, Timothy D.},
abstractNote = {Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere. X-ray Computed Tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and in-house developed code was used to non-invasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure, and extract quantitative information from the 3D data, respectively. Based on the explicitly-resolved root structure, pore-scale computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. Furthermore, the coupled imaging-modeling approach demonstrates a realistic platform to investigate rhizosphere flow processes and would be feasible to provide useful information linked to upscaled models.},
doi = {10.1016/J.RHISPH.2017.04.017},
journal = {Rhizosphere},
number = P2,
volume = 3,
place = {United States},
year = {2017},
month = {5}
}