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    Author(s): Christine Todoroki; Robert A. Monserud; Dean L. Parry
    Date: 2005
    Source: Forest Products Journal. 55(6): 38-47
    Publication Series: Scientific Journal (JRNL)
    PDF: Download Publication  (2.1 MB)


    The purpose of this study was threefold: 1) compare actual with simulated lumber yields; 2) examine the effect of measurement errors associated with knot angles and morphology. on lumber grade; and 3) investigate methods for predicting lumber quality within unsawn logs from surface knots. Twenty-eight Douglas-fir (Pseudotsuga menziesii(Mii irb.) Franco) logs were measured, mapped, sawn, and the lumber dried and graded. A corresponding set of digital log models was developed. Further sets that altered knot azimuth (within measurement error), rake (according to branch distributions ), and branch morphology (live or dead) were generated. All log models were processed in the sawing simulator AUTOSAW and the simulated lumber with knot defects was graded to Western Wood Products Association criteria (American Lumber Standards). The simulations showed that lumber grade is sensitive to knot angle, in particular azimuth, and even more so, to morphology. However, other factors not represented in this study have an additional effect on lumber grade. An index, Grade Average, was developed to quantify log quality in terms of lumber grades. In general Grade Average decreased with increasing mean knot diameter. This tendency was stronger for simulated grade yield (r2 ranging from 0.74 to 0.76) than actual (r2 = 0.26). Grade Average tended to over-predict when there were fewer than 10 surface knots, and to under-predict with smaller diameter logs. The relationship between actual and simulated Grade Average was quite poor (r2 ranging from 0.10 to 0.11). These results suggest that knowledge of the log surface knots alone is not enough to accurately predict internal lumber grade.

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    Todoroki, Christine, L.; Monserud, Robert A.; Parry, Dean L. 2005. Predicting internal lumber grade from log surface knots: actual and simulated results. Forest Products Journal. 55(6): 38-47

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