Optimization potential for perception-oriented appearance classification by simulated sawing of computed tomography-scanned logs of Norway spruce

Abstract

Wood, as a natural material, has favourable properties in both technical and aesthetic aspects. Due to its inherent variability, production of high-quality sawn timber demands adequate control of log conversion, which is feasible with computed tomography (CT) log scanning. Existing appearance grading rules for sawn timber might not fully reflect people's visual perception of wood surfaces, and therefore, an alternative, more perception-oriented appearance classification could be beneficial. An appearance classification of sawn timber based on partial least squares discriminant analysis (PLS-DA) of knot-pattern variables was developed and tested. Knot-pattern variables derived from images of board faces were used in training PLS-DA models against an initial classification of the board faces previously established by aid of cluster analysis. Virtual board faces obtained from simulated breakdown of 57 CT-scanned Norway spruce logs were graded according to the developed classification. Visual assessment of the grading results indicated that the classification was largely consistent with human perception of board appearance. An initial estimation of the potential to optimize log rotation, based on CT data, for the established appearance grades was derived from the simulations. Considerable potential to increase the yield of a desired appearance grade, compared to conventional log positioning, was observed.     

Between- and within-site variation of density and bending properties of Picea abies structural timber from Norway

This study provides an analysis on the variability of structural timber of Norway spruce (Picea abies) grown in Norway. Density, modulus of elasticity (MOE) and bending strength were measured on 1188 boards from 205 trees, sampled from 14 sites throughout Southern Norway, Eastern Norway and Trøndelag. The area represents the procurement area for the majority of Norwegian sawmills. The variability of the timber properties was analysed in a linear mixed model where the random variance was divided into variance due to site, variance due to trees and within-tree variance. Models describing variance due to site based on site index, altitude and latitude were developed, and combined with data from the Norwegian National Forest Inventory to estimate mean values and variability of the timber properties. The results showed that major parts of the variance due to site are explained by altitude and site index, and for density also by latitude. Major parts of the variance due to site and the variance due to trees in bending strength and MOE were explained by density.     

Predicting dynamic modulus of elasticity of Norway spruce structural timber by forest inventory,airborne laser scanning and harvester-derived data

Norway spruce structural timber is one of the most important products of the Norwegian sawmilling industry, and a high grade-yield of structural timber is therefore important for the economic yield. Presorting of logs suited for production of structural timber might be one option to increase the grade yield. In this study, dynamic modulus of elasticity (E_dyn) of structural timber was predicted based on forest inventory data at site level and single-tree data from airborne laser scanning (ALS) and harvester. The models were based on 611 boards from 4 sites in southeastern Norway. Important variables at site level were elevation, site index (SI), and mean stand age. However, when combining data from all information sources, mean stand age and site index were the only significant variables at site level. Tree height and variables describing the crown, like crown length and crown volume, were important vaiables extracted from ALS data. Stem diameter measures and tapering were important variables measured by the harvester. The combined model with variables from all three information sources reduced the variance the most, especially when using individual tree age instead of average stand age. However, combining all these data requires accurate positioning of the trees by the harvester.     

Structure of mixed Picea abies (L) Karst,and Betula pendula Roth and Betula pubescens Ehrh. stands in South and middle Sweden

Observed diameter distributions of forest stands are adapted to the Johnson S _b probability function. The stands investigated are untreated mixed stands of Norway spruce (Picea abies (L.) Karst.) and birch (Betula pendula Roth and Betula pubescens Ehrh.) aged between 20 and 32 years. The adaptation of the Johnson S_b probability function is made both on mixed spruce and birch, and on each species separately. Altogether 156 observations were tested with observed distributions against calculated distributions in the Kolmo‐gorov‐Smirnov test. The fractiles are predicted with multiple regression and two multivari‐ate techniques, simultaneous‐equation models (multivariate regression) and partial least squares with latent variables. The independent variables are characteristics of site and stand. Both multivariate methods predict diameter distribution well when tested.