Prediction of dry veneer stiffness using near infrared spectra from transverse section of green log

Abstract

This study examined the feasibility of near infrared spectroscopy as a novel technique for log assessment on the basis of wood property. Near infrared (NIR) spectra were obtained from the transverse section of green log and multivariate regression analysis was carried out to predict the stiffness of veneer processed from the log. The stiffness of the veneer was dynamic modulus of elasticity measured using ultrasonic method. The calibrations of veneer stiffness had moderate relationships between measured and NIR-predicted values, with regression coefficients ranging from 0.84 to 0.88. The calibration equations were applied to the test set and it was found that predictions were also well fitted, with regression coefficients ranging from 0.67 to 0.89. The results indicate that the variation of wood stiffness within the logs could be assessed using the NIR spectra from the cross-section of logs. The spectra were obtained from green condition of the log and the stiffness of veneer was measured after kiln drying. Thus, the results imply that the wood stiffness in dry condition could be predicted using the spectra collected from green logs. If the models obtained in this study put into the imaging system, the two-dimensional map of the stiffness would be visualized on the cross-section of logs. The NIR spectroscopy coupled with imaging system could compensate the weak point of the traditional methods for log assessment.