Predicting strength of Norway spruce and Scots pine sawn timber using discrete X-ray log scanning, optical board scanning, traceability, and partial least squares regression

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Abstract

Recently developed technology in sawmills such as advanced log scanning and traceability concepts enable new ways of grading logs and boards. When it comes to strength grading, this is often done on sawn boards using automatic scanning systems. However, if board scanners were to be augmented with data from log scanners by using traceability, more information on the wood properties is available. In this study, the main objective was to compare the strength prediction capability of board scanning alone, to board scanning augmented with X-ray and 3D data from log scanning, for Norway spruce (Picea abies L. Karst.) and Scots pine (Pinus sylvestris L.). In that case, data from three different scanning systems was combined, two for logs and one for boards. A further objective was to investigate whether pre-sorting logs for strength grading can be done using either 3D log data alone, or 3D log data augmented with X-ray data. The results show an improved strength prediction when adding log data to board data, and that 3D log data alone is not enough to pre-sort logs for strength, while adding X-ray log data makes it possible. Strength prediction on Scots pine performed somewhat better than prediction on Norway spruce.

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