Determination of terpene-based VOCs emitted from pine wood using NIR spectroscopy

Abstract

ABSTRACT In the search for a quick and less labor-intensive method for determining terpene emissions of high emitting wood like Pinus sylvestris, this study utilized near-infrared spectroscopy (NIR) combined with multivariate analysis methods and compared it to the standard measurement method according to the EN 16516 standard. The spectra were measured on the surface of solid-wood samples and correlated with the simultaneously determined air concentrations of terpenes. For α-pinene and 3-carene, prediction models were created using partial least squares regression (PLSR). Both work with determination coefficients of 0.77 and a Root Mean Square Error of Prediction (RMSEP) of 12% of the maximum emissions achievable in this study. A model based on the sum of the two terpenes was built and tested to determine the predictive capability of multiple similar substances simultaneously from the NIR recording. The model performs slightly worse, with a determination coefficient of 0.71 and RMSEP of 13%. Despite continuous expansion of the datasets for multiple models, no better metrics were achieved, likely because of the heterogeneous structure of wood when scanning a solid-wood surface. Systematic deviations were observed in particularly low reference ranges, which may indicate non-linearity in the relationship between terpenes and the NIR signal.