Estimation of density, moisture content and strength properties of Tectona grandis wood using Near Infrared Spectroscopy

Abstract

Near infrared spectroscopy is non-invasive and may be applied as a rapid and cost effective technique for assessment of quality parameters of timber. Near infrared spectra of Tectona grandis (teak) wood samples of were collected before measuring physical (density, equilibrium moisture content) and strength (flexural and compressive) properties using conventional methods. Partial least squares regression was used to develop calibration models between measured\xa0 wood properties and near infrared data. The best near infrared spectra pre-processing methods differed by property. Linear calibration models with high R², low error and high ratio of performance to deviation values were observed from partial least squares analysis for different wood properties. These linear models may be applied for rapid and precise estimation of the properties examined in testing and evaluation procedures for commercially valuable teak wood.