Prediction of board values in Pinus sylvestris sawlogs using x-ray scanning and optical three-dimensional scanning of stems

As the sawmill industry strives towards customer orientation, the need for sorting of logs according to quality has been recognized, and automatic sorting based on measurements by three-dimensional (3D) optical log scanners has been implemented at sawmills. There is even a small number of sawmills using the X-ray log scanner for automatic log-sorting. At the log-sorting stage, the potential of the raw material to fulfil the needs has already been reduced by the decisions taken when the trees were bucked (cross-cut) into logs. Thus, the application of predictions of the boards' properties at the bucking stage is desirable. This study investigates the possibility of predicting board values from logs based on 3D scanning alone and 3D scanning in combination with X-ray scanning of stems. This study is based on 628 logs scanned by computed tomography that make up the Swedish Pine Stem Bank. Simulated sawing of the logs gave product values for each log. Prediction models on product value were adapted using partial least squares regression and x-variables derived from the properties of the logs and their original stems, measurable with a 3D log scanner and the X-ray LogScanner. The results were promising. Using a 3D scanner alone, R-2 was 0.68, and using a 3D scanner in combination with an X-ray LogScanner, R-2 was 0.72.