Predicting the properties of structural timber using a rapid and reliable non-destructive
method is a critical quality control task in production. This study investigates using infrared …

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool
for predicting wood properties. When deploying NIR models, one faces challenges in …

Vis-NIR hyperspectral imaging was adopted to predict the moisture content (MC) of wood. A
total of 30 beech blocks were used in the experiments, each block was dried 7 times to …

Near‐infrared (NIR) spectroscopy provides a rapid alternative to traditional methods of wood
property assessment. For organizations who assess wood properties on a large scale …

ABSTRACT A chemistry-based explainable machine learning (ML) approach was used to
predict wood properties using near infrared (NIR) spectral data collected from rough and …

Air-dry density, modulus of rupture (MOR), modulus of elasticity (MOE), compressive
strength parallel to grain, and hardness of Catalpa bungei clones were investigated in this …

This study developed regional calibration models for the prediction of loblolly pine (Pinus
taeda) tracheid properties using near-infrared (NIR) spectroscopy. A total of 1842 pith-to …

This chapter describes the use of near-infrared spectroscopy for analysis of pulp and paper
products. It includes the concepts of analysis of pulp yield, wood chemistry, estimation of …

Near-infrared spectroscopy (NIRS) is a non-destructive method that has been used in wood
property assessment. Preliminary studies have revealed its ability to predict wood density …

Acacia, including Acacia hybrids, are some of the most important species grown as part of
the Vietnamese wood industry. Rapid methods to identify the variations in the wood …