Predicting moisture content of yellow-poplar (Liriodendron tulipifera L.) veneer using near infrared spectroscopy

On-line measurement of the moisture content (MC) of veneer sheets is paramount to process control in the veneer-based panel and engineered wood products industry. This study examined the feasibility of using near infrared (NIR) spectroscopy (800 to 2400 nm) combined with multivariate data analysis to predict MC of yellow-poplar veneer sheets. Multivariate data analysis employing principal component regression (PCR) and partial least squares regression (PLS1) analysis techniques indicated clustering of veneer samples of the same or close MC range with a clear distinction between samples of low and high MC. Both PCR and PLS1 veneer MC predictive models had correlations (R-2) greater than 0.94. The spectra window, 1400 to 1900 nm, between the two moisture peaks (1450 and 1930 nm) gave correlation coefficients (R-2) of 0.985 and 0.986 for PCR and PLS1, respectively. There is no clear distinction between the PCR and PLS1 models developed using the NIR spectra region of 1400 to 1940 nm. However, the PLS1 models with lower root mean square error of prediction (RMSEP), standard error of prediction (SEP) and Bias were better when compared to the PCR models developed using the whole NIR spectra region and restricted NIR spectra region not associated with the hydroxyl band.