pwat.0000451.t004 -

The optimization of biogas production from various organic wastes in anaerobic digestion relies on accurate mathematical models. Spectral methods offer a promising analytical approach for modeling process dynamics. This study assesses their performance in predicting substrate concentration, biomass growth, and biogas production, using Monod and Contois kinetics. Results are compared to conventional numerical methods, with experimental validation based on batch processes using cow dung, chicken manure, food and fruit waste, and treated agricultural straws. Pearson correlation coefficients between 0.788 and 0.989 confirm strong alignment between numerical and experimental data. Spectral methods also accurately capture the timing and magnitude of biogas production peaks. These findings highlight their effectiveness in providing reliable predictions across diverse digestion conditions. By modeling complex interactions within the system, spectral methods support improved process control and operational optimization, ultimately contributing to more efficient and sustainable biogas production.