Abstract
The ratio of biomass to plastic in wood plastic composites (WPCs) is very important for the development of WPCs. This paper investigates the feasibility of predicting the biomass and polypropylene (PP) contents in three WPC species (Chinese fir/PP, poplar/PP and bamboo/PP) using near-infrared (NIR) spectroscopy combined with partial least squares regression (PLS). Several spectra pretreatments were applied to improve the models. Compared to other methods, baseline correction data processing gave the optimal model. The results of external validation showed that the coefficient of determination (R 2), root mean square error of prediction (RMSEP) and the ratio of the standard deviation in the validation set to the RMSEP (RPD) were 0.930, 1.944 and 3.578 for biomass and 0.930, 1.958 and 3.587 for PP, respectively. It is concluded that NIR in combination with PLS is capable of reliable quantification of biomass and PP in a diversity of PP-based WPCs.
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