Solid-state fermentation is a widely applied bioprocess for biomass valorisation, enzyme production, and food biotechnology. The open, multi-phase nature of solid-state fermentation generates spatial heterogeneity in temperature, oxygen, moisture, and nutrients, which is essential for diverse microbial metabolism but also poses challenges for process stability, scale-up, and resource efficiency. To better quantify this phenomenon and enable subsequent process control, we characterised parameter variations and developed mathematical models by dividing the fermentation stack into three distinct layers, integrating heat and mass transfer with microbial growth kinetics, stoichiometric reactions, and metabolic heat for three dominant microbial groups across different layers. Collected industrial data revealed stratified heterogeneity of temperature, oxygen and moisture, with temperature serving as an obvious boundary indicator. Models can well predict temperature profile (R 2 > 0.82) and oxygen level (R 2 > 0.89), capturing temporal and spatial shifts of high-temperature zones, transitions from aerobic to anaerobic conditions and spatial microbial growth dynamics. This framework provides a quantitative basis for layer-specific monitoring and control strategies in solid-state fermentation, offering potential to enhance process stability, improve biomass utilization efficiency, and support sustainable scale-up of solid-state bioprocesses for bioresource and bioproduct applications. • Model links heat, mass transfer, and microbial growth in stacking fermentation. • Layer-specific temperature, oxygen, and moisture drive microbial dynamics. • Model predicts heat and mass transfer, and succession of microbes at different layers. • Modeling provides a tool to optimize stacking fermentation and product consistency.
Jin et al. (2026) studied this question.