Comparative Assessment of Fast Moisture Content Prediction Applying In-Line NIRS on Industrial Woodchip

The increased interest in environmental sustainability, driven by the transition to renewable energies, has spotlighted woodchip as an effective alternative to fossil fuel. Despite being readily available, its natural origin results in inherent heterogeneity, affecting every stage of the supply chain up to the combustion. Firstly, moisture content is detrimental for calorific value, leading to ineffective combustion drawbacks in transport and challenging storage. Water content monitoring along the production chain is crucial but its evaluation with standard analyses is limited due to destructive approach, unsuitable schedules and consequent costs. Near-infrared spectroscopy (NIRS), as an alternative technique, provides a non-destructive, repeatable, and faster method for both lab and inline control, overcoming standards limits. Considering the comparation already run with equal method, NIRS performances in predicting moisture content in Italian industrial woodchip simulating an in-line system are evaluated. Steady collection of continuous replicates improves woodchip representativeness, reducing estimation bias and enhancing prediction reliability (determination coefficient ~0.9, error <3%). Given the qualitative screening results, NIRS shows high water detection ability, acting as portable tool for real-time characterization in power plants. The immediate evaluation of water content could support critical steps along the supply chain, contributing to clean energy and market safety.