Predicting lumber grade and by-product yields for Scots pine trees

Abstract

The purpose of this study was to develop models for estimating yields of lumber grades and by-products of individual Scots pine ( Pinus sylvestris L.) trees using stem and crown dimensions as explanatory variables. Two separate data sets were used: (1) one simulated by the process-based growth model, PipeQual, which provides information about stem form and branch properties. The model was used to predict the 3D structure of Scots pine stems from thinning regimes of varying intensity and rotation periods and (2) an empirical data set with detailed 3D measurements of stem structure. The stems were sawn using the WoodCim sawing simulator and the yields and grades of the individual sawn pieces, as well as by-products, were recorded. The sawn timber was classified on A, B, C and D-grades for side and centre boards separately (Nordic Timber grading). By-products were pulpwood, sawmill chips, sawdust and bark. The response variables were formulated as proportions of the total volume of each stem. Multinomial logistic regression models using pulp wood proportion as a reference category were developed based on both data sets separately, and each model was tested on the other data set not used in model building. We found that the proportions of A and B grade lumber and pulp wood were inaccurately predicted. By combining data sets we formulated more accurate models. In combined data set's models, the best combination of explanatory variables was diameter of the stem at the breast height, its logarithmic transformation, the height of the living crown (distance from ground to lowest living branch) and the height of the lowest dead branch (branch diameter ≥1.5 cm). The developed approach integrates implications of forest management for the quality of round wood and sawn wood conversion chain. The models can be used to optimize stand management with respect to the value of potential sawmill products.