With the growing global demand for renewable energy and the increased use of forest residues left behind or burned after harvesting, the wood pellet industry is looking into optimizing feedstock. While using forest biomass holds great promise, it also brings challenges such as contamination, ash and moisture content variability and higher processing costs. The Wood Pellet Association of Canada (WPAC) and The University of British Columbia’s Biomass and Bioenergy Research Group (BBRG) are developing Artificial Intelligence (AI) assisted Near-Infrared (NIR) technology specifically for use in the wood pellet sector. This tool could significantly improve the efficiency of biomass sorting, leading to higher-quality pellets and reduced operational costs. …NIR technology operates by shining near-infrared light on biomass feedstock and analyzing the light reflected to determine molecular composition. This allows real-time measurement of key properties, including moisture content, chemical composition, particle size, contaminants and impurities.