Computed tomography (CT) scanning of internal log attributes prior to sawing increases lumber value in white spruce (Picea glauca) and jack pine (Pinus banksiana)

The increased pressure on timber supply due to a reduced forest land base urges the development of new approaches to fully capture the value of forest products. This paper investigates the effects of knowing the position of knots on lumber volume, value, and grade recoveries in curve sawing of 31 white spruce (Picea glauca (Moench) Voss) and 22 jack pine (Pinus banksiana Lamb.) trees. Internal knot position was evidenced by X-ray computed tomography (CT) imaging, followed by the application of a knot-detection algorithm allowing log reconstruction for use as input in the Optitek sawing simulation software. Comparisons of the three levels of sawing optimization (sweep up, shape optimized, and knot optimized) revealed that considering internal knots before log sawing (e.g., knot optimized) generated 23% more lumber value for jack pine and 15% more for white spruce compared with the traditional sweep-up sawing strategy. In terms of lumber quality, the knot-optimized strategy produced 38% more pieces of grade No. 2 and better in jack pine and 15% more such pieces in white spruce compared with the sweep-up strategy. These results indicate a great potential to increase manufacturing efficiency and profitability by implementing the CT scanning technology, which should aid in developing a strong bioeconomy based on an optimized use of wood.