Rotating Pinus sylvestris Sawlogs by Projecting Knots from X-ray Computed Tomography Images onto a Plane

Magnus Fredriksson, Erik Johansson, Anders Berglund


In this paper, a method for utilizing knot information from computed tomography (CT) scanning of Scots pine (Pinus sylvestris L.) logs was evaluated. A high speed industrial CT scanner is being developed, which will enable scanning of logs in sawmills at production speed. This development calls for the ability to optimize breakdown parameters in a quick manner because there are many decisions to be made and the timeframe for these production decisions is short. One of the important breakdown parameters is in which rotational position to saw a log. The presented method used CT data to create a two-dimensional projection of knot information from a log, in order to minimize the amount of data to analyze. The center of mass of the knot projection relative to the center of the sawing pattern was chosen as the rotational position of the log. The aim was to put large knots on the flat surfaces of the boards, as knots on edge surfaces have a more negative effect on board quality in the sorting rules used in this study. The method was tested by sawing simulation and was compared with the industrial praxis of sawing logs horns down. The results show an increase in board quality and value, albeit for a selected group of Scots pine logs. The method is very sensitive to positioning errors, but it has some potential if sawlog positioning accuracy is improved.


CT scanner; Knot; Log rotation; Sawing simulation; Sawmill

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Welcome to BioResources! This online, peer-reviewed journal is devoted to the science and engineering of biomaterials and chemicals from lignocellulosic sources for new end uses and new capabilities. The editors of BioResources would be very happy to assist you during the process of submitting or reviewing articles. Please note that logging in is required in order to submit or review articles. Martin A. Hubbe, (919) 513-3022,; Lucian A. Lucia, (919) 515-7707, URLs:; ISSN: 1930-2126