Estimating wood moisture by near infrared spectroscopy: testing acquisition methods and wood surfaces qualities

Abstract

Moisture is one of the most important wood properties because its variation directly influences the material strength and density. Thus, the aim of this study was to develop near infrared (NIR) spectroscopic models in order to estimate the moisture content in wood specimens. Moreover, predictive models built from NIR signatures recorded by different acquisition methods and on wood surfaces were compared and discussed. Mass and NIR spectra were measured on forty (40) Eucalyptus wood specimens in 10 steps during drying from the fiber saturated point to anhydrous condition. NIR spectra were recorded by means of an integrating sphere and optical fiber probe on four surface. Thus, wood moisture values were correlated with the corresponding NIR spectra by Partial Least Squares (PLS) Regression. The best models for estimating wood moisture were developed from NIR spectra recorded on the transverse surface produced with the band saw by integrating sphere method (R²p = 0.96 and RMSEP = 8.56%) and fiber optic probe (R²p = 0.83 and RMSEP = 20.09%). Therefore, NIR spectrum recorded by integrating sphere taken on transverse or radial wood surface cut by band saw are the most suitable for generating NIR models for estimating the moisture content in Eucalyptus wood.