Authors
Abstract
A log-level lumber grade assessment method based on branchiness was developed to bring lumber grade considerations into forest management planning. Existing methods focus primarily on mean or maximum knot size per log. The method developed in this study is based on branch size and location on log surface, internal knot shape, and log size. Assuming a cylindrical log shape with a central pith, a log transformed linear regression model was developed to predict minimum horizontal branch angle (branch azimuth) between successive knots, with respect to log size, that would produce at least one piece of lumber at a desired grade, by product, from the center cant using either an edge or centerline knot pattern. The minimum difference in horizontal branch angle between successive branches decreased with increasing log size if product specifications were held constant and increased with increasing product width if log size remained constant. The above method was demonstrated using a sample of logs from three initial spacings (1.8 m, 2.7 m, and 3.6 m). Although lumber grade recovery improvement potential varied from percent to 40 percent across spacings, no clear trend was evident for improvement potential by spacing at the product and grade level based on a chi-square analysis using a 2 x 3 contingency table ([[chi square].sub.0.05,3] = 7.815, [[chi square].sub.edge] = 3.979, and [[chi square].sub.centerline] = 2.392).
Forest Products Journal
