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Title: Low-field magnetic resonance imaging of roots in intact clayey and silty soils

Abstract

The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T2 (4 ms) and the typical root water relaxation time T2 (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-Dmore » MRI projection images were produced of roots with a diameter range of 1.5–2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. In addition, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.« less

Authors:
; ; ; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Texas A & M University, College Station, TX (United States). Texas A & M AgriLife Research
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
OSTI Identifier:
1615698
Alternate Identifier(s):
OSTI ID: 1799099
Grant/Contract Number:  
AR0000823
Resource Type:
Published Article
Journal Name:
Geoderma
Additional Journal Information:
Journal Name: Geoderma Journal Volume: 370 Journal Issue: C; Journal ID: ISSN 0016-7061
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English
Subject:
58 GEOSCIENCES; Agriculture; LF-MRI: Low Field Magnetic Resonance Imaging; HF-MRI: High Field Magnetic Resonance Imaging; MR: Magnetic Resonance; MRI: Magnetic Resonance Imaging; NMR; Nuclear Magnetic Resonance; RF: Radio Frequency; SNR: Signal to Noise Ratio; AUTOMAP: Automated Transform by Manifold Approximation; OD: Outside Diameter; AWG: American Wire Gauge; IFFT: Inverse Fast Fourier Transform; FFT: Fast Fourier Transform

Citation Formats

Bagnall, G. Cody, Koonjoo, Neha, Altobelli, Stephen A., Conradi, Mark S., Fukushima, Eiichi, Kuethe, Dean O., Mullet, John E., Neely, Haly, Rooney, William L., Stupic, Karl F., Weers, Brock, Zhu, Bo, Rosen, Matthew S., and Morgan, Cristine L. S. Low-field magnetic resonance imaging of roots in intact clayey and silty soils. Netherlands: N. p., 2020. Web. doi:10.1016/j.geoderma.2020.114356.
Bagnall, G. Cody, Koonjoo, Neha, Altobelli, Stephen A., Conradi, Mark S., Fukushima, Eiichi, Kuethe, Dean O., Mullet, John E., Neely, Haly, Rooney, William L., Stupic, Karl F., Weers, Brock, Zhu, Bo, Rosen, Matthew S., & Morgan, Cristine L. S. Low-field magnetic resonance imaging of roots in intact clayey and silty soils. Netherlands. https://doi.org/10.1016/j.geoderma.2020.114356
Bagnall, G. Cody, Koonjoo, Neha, Altobelli, Stephen A., Conradi, Mark S., Fukushima, Eiichi, Kuethe, Dean O., Mullet, John E., Neely, Haly, Rooney, William L., Stupic, Karl F., Weers, Brock, Zhu, Bo, Rosen, Matthew S., and Morgan, Cristine L. S. Wed . "Low-field magnetic resonance imaging of roots in intact clayey and silty soils". Netherlands. https://doi.org/10.1016/j.geoderma.2020.114356.
@article{osti_1615698,
title = {Low-field magnetic resonance imaging of roots in intact clayey and silty soils},
author = {Bagnall, G. Cody and Koonjoo, Neha and Altobelli, Stephen A. and Conradi, Mark S. and Fukushima, Eiichi and Kuethe, Dean O. and Mullet, John E. and Neely, Haly and Rooney, William L. and Stupic, Karl F. and Weers, Brock and Zhu, Bo and Rosen, Matthew S. and Morgan, Cristine L. S.},
abstractNote = {The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T2 (4 ms) and the typical root water relaxation time T2 (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-D MRI projection images were produced of roots with a diameter range of 1.5–2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. In addition, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.},
doi = {10.1016/j.geoderma.2020.114356},
journal = {Geoderma},
number = C,
volume = 370,
place = {Netherlands},
year = {Wed Jul 01 00:00:00 EDT 2020},
month = {Wed Jul 01 00:00:00 EDT 2020}
}

Journal Article:
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https://doi.org/10.1016/j.geoderma.2020.114356

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