THE INFLUENCE OF WOOD QUALITY ON LUMBER DRYING DISTORTION

Commercial experience with the sawing of logs from fast-grown plantati ons has shown that there can be significant drying distortion associat ed with the presence of juvenile wood. In New Zealand this is a growin g concern due to the reduction of rotation ages for radiata pine (Pinu s radiata D Don) to around 25-30 years. The purpose of this analysis w as to use the results of sawing studies to identify some of the major factors affecting distortion of the final product (structural lumber i n this case) and test the feasibility of modeling the relationships. A nalyses of some 9 000 individual boards (100 x 40 and 100 x 50 mm) fro m 1 000 logs indicated the need to take into account a range of factor s relating to the raw material (logs), secondary processing technology (sawing pattern, drying method and the influence of planing), product (lumber dimensions) and standards (grading rules). The strong propens ity for lumber from small diameter and physiologically young logs to d egrade was confirmed and over 90% of the problem was related to twist rather than crook or bow. In the worst cases (small juvenile logs, low temperature drying, no planing) up to 80% of the boards were categori zed as 'rejects'. At the other extreme, large diameter mature logs dri ed according to recommended practices and those that were machined to final size showed around a 5% rate of rejection. Diameter was shown to be the most influential log property. Spiral grain was also important due to its influence on twist during drying; it is greatest in juveni le wood which forms a greater proportion in small diameter logs. The a nalyses showed that both diameter and spiral grain are related to twis t. Unfortunately, spiral grain is a little known feature of plantation pines, and is only now gaining the research attention it deserves. Th e results presented here indicate that log diameter of radiata pine is a good indicator of the propensity for lumber to twist during drying. Since this can be predicted using forest management models, it is pro posed to extend the capability of predictive models by modifying them to assess the yields of dried, finished products.