Recent Advances in Food Process Engineering

Drying remains one of the most energy-intensive unit operations in food manufacturing, and the pressure to decarbonise process heat has pushed the field beyond incremental improvement of convective dryers towards four partly overlapping strategies: hybridisation of heat-transfer mechanisms, recovery of thermal energy that conventional dryers discard, substitution of fossil-derived heat with renewable supply, and replacement of experience-based operation with sensor-driven, model-based control. This critical narrative review examines how far the evidence for each strategy has matured, where the four strands reinforce one another, and where the literature has advanced claims that the underlying studies do not sustain. Peer-reviewed research published between 2018 and mid-2026 was located through open scholarly indexes and citation searching, appraised for methodological adequacy, and synthesised thematically rather than catalogued. The evidence is strongest and most internally consistent for hybrid electromagnetic-convective configurations, which shorten drying time substantially and often improve energy efficiency, and for heat-pump and exhaust-stream recovery, where thermodynamic accounting is comparatively transparent. It is weaker for renewable-integrated dryers, where performance is reported under climate-specific conditions that limit transferability, and weakest for intelligent control, where most contributions demonstrate predictive accuracy on retrospective data rather than closed-loop benefit on operating plant. Three problems recur across the field: incompatible energy indicators that prevent quantitative comparison, evaluation at laboratory scale under conditions that favour the novel configuration, and quality assessment restricted to a narrow set of physical and antioxidant indicators. The synthesis argues that the principal barrier to next-generation drying is no longer the availability of individual technologies but the absence of shared measurement conventions, validated real-time sensing, and independent evaluation at production scale. Priorities are proposed for reporting standards, sensor development, controller validation and context-sensitive techno-economic assessment.