Non-destructive evaluation of wood stiffness and fiber coarseness, derived from SilviScan data, via near infrared hyperspectral imaging

Abstract

Near infrared hyperspectral imaging combined with partial least squares regression analysis was used to evaluate wood stiffness (modulus of elasticity) and fiber coarseness. Five samples with normal wood and compression wood collected from two Japanese Cedar ( Cryptomeria japonica) trees were analyzed. To achieve high reliability of the prediction values, a SilviScan system (X-ray densitometry, X-ray diffractometry, and optical microscopy) with the high spatial resolution was used for measuring reference data. The measurement interval for modulus of elasticity and fiber coarseness was 1 mm and 25 µm, respectively. After spectral pre-treatment and key wavelengths selection, partial least squares analysis was applied to calibrate near infrared data to reference values. The determination coefficient ( RCV2) of modulus of elasticity was 0.66 with a root mean square error of cross validation (RMSECV) of 1.80 GPa. For the constructed fiber coarseness calibration model, RCV2 and RMSECV were 0.62 and 35.02 µm/g, respectively. Finally, modulus of elasticity and fiber coarseness mapping results show detailed information (156 µm/pixel) at the grown ring level. The differences among earlywood, latewood, and compression wood were all well identifiable.