Three-Dimensional Exploration of Soft-Rot Decayed Conifer and Angiosperm Wood by X-Ray Micro-Computed Tomography.

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Title: Three-Dimensional Exploration of Soft-Rot Decayed Conifer and Angiosperm Wood by X-Ray Micro-Computed Tomography.
Authors: Koddenberg, Tim1 (AUTHOR) tim.koddenberg@uni-goettingen.de, Zauner, Michaela1 (AUTHOR), Militz, Holger1 (AUTHOR)
Source: Micron. Jul2020, Vol. 134, pN.PAG-N.PAG. 1p.
Abstract: • The three-dimensional study of decayed wood is difficult to realize with common microscopy. • X-ray computed tomography is used to visualize the internal structure of wood after soft-rot decay. • The elemental characterization of inorganic particles is achieved through SEM-EDX. • Three-dimensional visualizations reveal fungal-induced cavities and spatial distribution of inorganic particles in decayed wood. X-ray micro-computed tomography (XμCT) was used to explore the decomposed structure of conifer and angiosperm wood after colonization by soft-rot fungi. The visualization of degradation features of soft-rot decay was challenging to achieve through XμCT. Difficulties in visualization emerged due to a decreased grayscale contrast (i.e. X-ray density) of the degraded wood. Nevertheless, we were able to image fungal-induced cell deformations in earlywood and cavities in the thick wall of latewood cells in three-dimensions (3D). Unlike the organic wood material, the higher X-ray density of inorganic deposits, identified as mainly calcium-based particles by energy-dispersive spectroscopy, allowed a facilitated 3D survey. The visualization of inorganic particles in 3D revealed a localized distribution in certain cells in conifer and angiosperm found mostly in earlywood. [ABSTRACT FROM AUTHOR]
Copyright of Micron is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Three-Dimensional Exploration of Soft-Rot Decayed Conifer and Angiosperm Wood by X-Ray Micro-Computed Tomography.
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– Name: Abstract
  Label: Abstract
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  Data: • The three-dimensional study of decayed wood is difficult to realize with common microscopy. • X-ray computed tomography is used to visualize the internal structure of wood after soft-rot decay. • The elemental characterization of inorganic particles is achieved through SEM-EDX. • Three-dimensional visualizations reveal fungal-induced cavities and spatial distribution of inorganic particles in decayed wood. X-ray micro-computed tomography (XμCT) was used to explore the decomposed structure of conifer and angiosperm wood after colonization by soft-rot fungi. The visualization of degradation features of soft-rot decay was challenging to achieve through XμCT. Difficulties in visualization emerged due to a decreased grayscale contrast (i.e. X-ray density) of the degraded wood. Nevertheless, we were able to image fungal-induced cell deformations in earlywood and cavities in the thick wall of latewood cells in three-dimensions (3D). Unlike the organic wood material, the higher X-ray density of inorganic deposits, identified as mainly calcium-based particles by energy-dispersive spectroscopy, allowed a facilitated 3D survey. The visualization of inorganic particles in 3D revealed a localized distribution in certain cells in conifer and angiosperm found mostly in earlywood. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Micron is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.micron.2020.102875
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