Predicting lumber grade and by-product yields for standing scots pine trees

The purpose of this study was to develop models for estimating yields and grades of lumber, as well as by-products, of individual Scots pine (Pinus sylvestris L.) stems using stem and crown dimensions as explanatory variables. The process-based growth model, PipeQual, which provides information about stem form and branch properties, was used to generate the material for analysis. The model was used to predict the 3D structure of Scots pine stems in thinning regimes of varying intensity and rotation periods. The generated 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 center boards separately (in accordance with Finnish export rules). By-products were pulpwood, sawmill chips, sawdust, and bark. The response variables were formulated as cumulative proportions of the total volume of each stem. Logistic regression models were fitted to the data, and the best combination of the explanatory variables was found to be living crown height and the natural logarithm of diameter at breast height. The models were tested against simulated sawing of actual measured Scots pine stems and predictions for larger stems were found to be more biased than those used in model building. The developed approach integrates wood production and the conversion chain. The models can be used in stand management optimization for comparing different management options, e.g., on a value-added basis from the sawmill's point of view.