Effect of knots and holes on the modulus of elasticity prediction and mapping of sugi (Cryptomeria japonica) veneer using near-infrared hyperspectral imaging (NIR-HSI)

Abstract

Naturally occurring knots reduce the mechanical strength of wood. Veneers from sugi (Cryptomeria japonica) served as research material to study the effect of knots and holes. Veneer samples were first subjected to a three-point bending test to obtain measured modulus of elasticity (MOE) values. Then, near-infrared (NIR) hyperspectral imaging (HSI) was used to construct a prediction model and map the predicted MOE values. This is the first attempt for MOE prediction from the entire veneer surface based on NIR-HSI technology, while the mathematical part relies on chemometrics and cross-validation partial least squares regression (CV-PLSR). Maps of MOE prediction values could distinguish between latewood (LW) and earlywood (EW), as well as between a sound knot and a dead knot.

Characterization and Prediction of Mechanical and Chemical Properties of Luanta Fir Wood with Vacuum Hydrothermal Treatment

“…Higher values indicate greater accuracy. If RPD = 1.0–2.5, the model can be used for wood grading [ 64 , 65 , 66 ]. Figure 5 reveals that the RPDs of the σ c,max , σ s,max , hardness, and MOR models were 1.49, 1.24, 1.13, and 2.39, i.e., all between 1.0 and 2.5; thus, these four models could be used for grading.…”

Comparative Performance of NIR-Hyperspectral Imaging Systems

“…Wood degradation either by fungi [32] or weathering processes [33][34][35] and treatments to protect wood, including acetylation [36,37], oil impregnation [38], thermal modification [39], and the concentration of phosphorus-based flame retardants [40], have all been investigated. Hyperspectral images have also been used for species classification [41,42], characterization of juvenile and mature wood [43], particleboard identification [44], and to investigate how the presence of knots and holes influences veneer modulus of elasticity [45]. On-line applications include the identification of wood chips with elevated extractive levels [46], the segregation of waste materials (including wood) [47][48][49] and monitoring the quality of extruded wood-plastic composites [50].…”