Monitoring of moisture content and basic specific gravity in black spruce logs using a hand-held MEMS-based near-infrared spectrometer

Abstract

Our study presents results of a test of a hand-held micro-electro-mechanical system (MEMS)-based near-infrared (NIR) spectrometer to estimate moisture content and basic specific gravity of black spruce frozen and unfrozen logs. The spectra were acquired on sapwood and heartwood as well as on tangential and transversal log sections. Partial least square regression was used to develop and validate the models that relate NIR spectral data to the log properties. Models were developed for the frozen and unfrozen logs separately (temperature-specific models) and for both kinds of logs together (generalized model). Both model types gave similar prediction accuracy and there were no temperature condition effects on the PLS model, for both moisture content and basic specific gravity estimation. This implies that the NIR spectrometer can be used whatever the log temperature conditions, even under freezing conditions.