The growing global demand for sustainable energy has intensified interest in biomass residues as viable feedstocks for biofuels and bio-based production. This review systematically examines advances in the utilization of biomass residues, spanning upstream assessment through downstream conversion pathways. Using the PRISMA framework, 543 peer-reviewed articles published between 1990 and 2025 were analyzed from the Scopus and Web of Science databases. The review reveals a clear methodological evolution from early residue characterization and physicochemical analyses toward integrated techno-economic, environmental, and system-level assessments. Upstream research increasingly addresses feedstock identification, spatial dispersion, logistics optimization, and pretreatment efficiency, while downstream advances focus on biochemical, thermochemical, and hybrid conversion technologies. Although artificial intelligence and machine learning constitute approximately 2.5–3% of the total historical literature, they account for nearly 18–22% of recent studies in process modeling and yield prediction, achieving predictive accuracies frequently exceeding R2 > 0.95. Despite these advances, persistent challenges remain in biomass logistics, feedstock heterogeneity, and technology scaling. Emerging trends highlight hybrid frameworks that integrate data-driven and mechanistic models to enhance efficiency, circularity, and commercial feasibility in bioenergy systems.
Kabir et al. (Wed,) studied this question.