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Non-destructive wood identification using X-ray µCT scanning: which resolution do we need?

Sofie Dierickx1,2,3, Siska Genbrugge4, Hans Beeckman5

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X-ray computed micro-tomography (µCT) offers a non-destructive method for wood identification. Optimal resolution for distinguishing anatomical features in wood samples using µCT is approximately 3 µm, though other resolutions also show potential.

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Area of Science:

  • Wood anatomy
  • Paleoecology
  • Cultural heritage studies
  • Wood trade

Background:

  • Traditional wood identification relies on anatomical features but often requires destructive sampling.
  • X-ray computed micro-tomography (µCT) presents a non-destructive alternative for visualizing internal wood structures.
  • A standardized resolution for wood identification using µCT is currently lacking.

Purpose of the Study:

  • To compare the effectiveness of different X-ray µCT resolutions for wood identification.
  • To determine the optimal resolution for distinguishing key anatomical features in African wood species.

Main Methods:

  • 17 African wood species were scanned using X-ray µCT at four resolutions: 1 µm, 3 µm, 8 µm, and 15 µm.
  • Scanned features were compared against established anatomical descriptions and images from the Inside Wood Online Database.
  • The distinguishability and measurability of standardized anatomical features were assessed at each resolution.

Main Results:

  • High resolutions (e.g., 1 µm) excel at visualizing small anatomical features like pits and fibers.
  • Low resolutions offer a larger field of view, ideal for observing large-scale features such as vessel porosity and arrangement.
  • An intermediate resolution of 3 µm proved optimal for recognizing a comprehensive range of anatomical features, facilitating wood identification.

Conclusions:

  • X-ray µCT is a viable technique for non-destructive wood identification.
  • All tested resolutions provide valuable anatomical information, with 3 µm offering the highest potential for identification.
  • A publicly available dataset of scanned wood species is provided to promote the systematic use of µCT in wood identification.