Feasibility of Near-Infrared Spectroscopy for On-Line Grading of Sawn Lumber

Abstract

Near-infrared (NIR) spectroscopy, coupled with multivariate analysis, has been used to evaluate the wood properties of sawn lumber of Japanese larch (Larix kaempferi), whose diffuse reflection spectra were acquired under static and moving conditions. Prediction models of the dynamic modulus of elasticity (E(fr)), the modulus of elasticity in bending tests (E(b)), the bending strength (F(b)), the wood density (DEN), and the moisture content (MC) were developed using partial least squares (PLS) analysis. For all wood properties, models obtained from data collected under the moving condition as an analogue of on-line measurement were superior to those from the static condition data. The regression coefficients for the PLS models predicting the mechanical properties in both static and moving conditions showed clear peaks at the absorption bands due to the three major polymers of wood, i.e., cellulose, hemicellulose, and lignin. NIR spectroscopy has high potential for the on-line grading of sawn lumber.