Estimating the density of coast Douglas-fir wood samples at different moisture contents using medical X-ray computed tomography

Wood density (ρ) is an indicator of Douglas-fir (Pseudotsuga menziesii) forest product performance and past and present tree ecophysiology. Models describing the spatial variation in this wood property will require a considerable sampling effort. Medical X-ray computed tomography (CT) has been identified as one technology for rapidly estimating ρ of Douglas-fir wood. The density of Douglas-fir can be predicted from CT Hounsfield units through a linear relationship (R2:96%). The moisture content of wood samples has an additional linear effect on estimating Douglas-fir wood density (0.0015g/cm3) and also has a practically minor (2.8E-06g/cm3), but significant, interactive relationship with CT Hounsfield units. While the effect of moisture content explains only a small percentage of the variance in ρ, accounting for this effect my be important to avoid prediction biases. Finally, X-ray tube current (mA) may also impose a small effect (0.00003g/cm3) on estimating wood density. In contrast to other factors, the filtered back-projection algorithm used to produce CT scanning images does not have an strong effect on estimating ρ. While it is important to account for scanner settings and moisture content, 74% of the variance in predicting ρ can be explained by CT Hounsfield units with 21% explained by accounting for moisture content and X-ray tube current. Independent estimates of wood sample volume for validation can be achieved in several ways, each with possible systematic biases. This experiment found volume of wood samples conditioned to different moisture content could be estimated similarly using volumetric displacement or dimension measurement by caliper. The absolute mean deviance of estimated sample volume from caliper measurement relative to volumetric displacement was 0.45cm3 or 2.6%. CT scanning can be used to rapidly estimate Douglas-fir at a resolution of 1-mm using unprepared samples.