Summary -Commercial experience with the sawing of logs from fast-grown plantations has shown that there can be significant drying distortion associated with the presence of juvenile wood. In New Zealand this is a growing concern due to the reduction of rotation ages for radiata pine (Pinus radiata D Don) to around 25-30 years. The purpose of this analysis was to use the results of sawing studies to identify some of the major factors affecting distortion of the final product (structural lumber in this case) and test the feasibility of modeling the relationships. Analyses of some 9 000 individual boards (100 x 40 and 100 x 50 mm) from 1 000 logs indicated the need to take into account a range of factors 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 propensity for lumber from small diameter and physiologically young logs to degrade 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 categorized as 'rejects'. At the other extreme, large diameter mature logs dried 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 juvenile wood which forms a greater proportion in small diameter logs. The analyses showed that both diameter and spiral grain are related to twist. Unfortunately, spiral grain is a little known feature of plantation pines, and is only now gaining the research attention it deserves. The 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 proposed to extend the capability of predictive models by modifying them to assess the yields of

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