169
Views
1
CrossRef citations to date
0
Altmetric
Brief Original

X-ray computed tomography for the detection of damage in Scots pine trunks caused by blister-rust fungus Cronartium pini (Willd.)

ORCID Icon, , ORCID Icon, , , & ORCID Icon show all
Pages 1022-1024 | Received 26 Aug 2022, Accepted 31 Aug 2022, Published online: 18 Sep 2022
 

ABSTRACT

Scots pine blister rust is a damaging fungus in pine forests, and in recent decades the disease has become a severe problem in Northern Fennoscandian Peninsula and makes the use of Scots pine wood as sawn timber problematic. The present study shows that it is possible to use X-ray computed tomography (CT) to detect blister-rust infection and damage caused by the fungus in green Scots pine trunks. Such damage is evidenced in the CT images as a reduction in moisture content and an increase in resin deposition in the green sapwood. The trunk cross-section may also be deformed as an effect of the infection. The heartwood has, however, image characteristics similar to those of the infected regions, and dedicated image-analysis algorithms are required for separation. Given the development of such algorithms, X-ray CT can become a powerful tool for blister-rust detection and further grading of sawn timber.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Gunnar Hedlunds Hedersfond through Norras Forskningsstiftelse [grant number 2021:03].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 182.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.