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Resin accumulation (resinwood) in Scots pine timber resulting from Cronartium pini infection represents an important quality defect, substantially reducing sawn yield and economic value in sawmilling. Current timber-grading standards detect resinwood solely through surface characteristics on sawn timber, risking undetected internal deposits until after processing. This study evaluated X-ray computed tomography (CT) for non-destructive resinwood detection across wood moisture states. Scots pine specimens exhibiting external cankers were harvested and scanned using an industrial CT scanner in both green and dry states, included full logs and 3-cm-thick discs. Comparative density analysis identified regions of interest based on elevated density patterns. Validation via acetone extraction quantified resin content in CT-identified resinwood zones versus unaffected wood. CT imaging revealed three characteristic resinwood signatures: (1) growth-ring distortions, (2) non-concentric cambial development, and (3) resin-saturated parenchyma with ground-glass opacity (GGO). Resinwood regions maintained significantly elevated radiographic density in both moisture states. Extraction confirmed substantially higher resin content within CT-identified areas. This moisture-state comparison provides a basis for developing automated CT detection methods in sawmills. These distinct radiographic features offer essential descriptors for detection algorithms, promising enhanced yield and value recovery through minimised resinwood-related defects.
Joevenller et al. (Wed,) studied this question.