Mechanistic insights into thermophilic anaerobic digestion of food waste: Linking macromolecular composition, microbial community dynamics, and biomethane production kinetics

This study investigated how the carbohydrate, protein, and fiber composition of food waste affects thermophilic anaerobic digestion (AD) using an integrated mixture-regression, Contois kinetic, and metagenomic approach. Batch experiments employed single, binary, and ternary substrate formulations with different macromolecular compositions. Time-resolved chemical oxygen demand (COD), volatile fatty acid (VFA), methane, and CO 2 profiles were monitored to assess substrate degradation and gas evolution. Biochemical pathways were represented by interconnected ordinary differential equations based on Contois kinetics, while bacterial, archaeal, and fungal communities were characterized through metagenomic sequencing. The mixture-regression models showed strong statistical adequacy and predictive performance, confirming that substrate composition significantly controlled hydrolytic-acidogenic activity, methanogenic kinetics, and biogas productivity. Carbohydrate- and protein-rich substrates accelerated hydrolysis and acidogenesis. In the carbohydrate–protein fraction, COD rapidly decreased from approximately 38,000 to below 18,000 mg L −1 within 54 days, while protein-rich systems accumulated approximately 4000–4400 mg L −1 VFA by days 30–35. Fiber-rich substrates degraded more slowly but steadily because of gradual lignocellulosic hydrolysis. Despite slower initial conversion, fiber-containing systems achieved the highest cumulative methane yield, reaching 800 mL CH 4 g −1 VS, by sustaining substrate release and limiting inhibitory metabolite accumulation. Metagenomic analysis revealed composition-dependent microbial selection, including enrichment of fermentative Lactobacillaceae and Clostridiaceae, hydrolytic Bacillaceae and Oscillospiraceae, and methanogenic Methanosarcinaceae and Methanotrichaceae. These findings provide mechanistic guidance for rational feedstock formulation and optimization of thermophilic AD, supporting sustainable waste valorization, renewable energy production, and UN Sustainable Development Goals 7, 12, and 13 through improved process stability, resource recovery, and mitigation of associated greenhouse gas emissions.