Predicting spiral grain by computed tomography of Norway spruce

Abstract

Spiral grain is a feature of wood that affects the shape of the sawn timber. Boards sawn from logs with a large spiral grain have a tendency to twist when the moisture content changes. The aim of this study was to investigate the possibility of predicting spiral grain based on variables that should be measurable with an X-ray LogScanner. The study was based on 49 Norway spruce (Picea abies) logs from three stands in Sweden. The logs were scanned with a computed tomography (CT) scanner every 10mm along the log. Concentric surfaces at various distances from the pith were then reconstructed from the stack of CT images. The spiral grain angle was measured in these concentric surface images, and a statistical model for predicting spiral grain was calibrated using partial least squares (PLS) regression. The PLS model predicts the spiral grain of a log at a distance 50mm from the pith based on different variables that should be measurable with an industrial X-ray LogScanner. The result was a PLS model withR ²=0.52 for the training set andR ²=0.37 for the test set. We concluded that it should be possible to predict the spiral grain of a log based on variables measured by an industrial X-ray LogScanner. The most important variables for predicting spiral grain were measures of sapwood content, variation in the ratio between the heartwood and log areas, and the standard deviation for the mean log density in 10mm thick cross slices along the log. The accuracy when sorting the logs into two groups with spiral grain of ≥2.0° and of <2.0°, respectively, was 84% of the correctly sorted logs.