Valorization of agro-food waste through anaerobic digestion (AD) is gaining prominence as alternative method of waste minimization and renewable energy production. The aim of this study was to identify the key parameters for digester performance subjected to kinetic study and semicontinuous operation. Biochemical methane potential (BMP) tests were conducted in two different operating conditions: without mixing (WM) and continuous mixing (CM). Three different substrates, including food waste (FW), chicken dung (CD), and codigestion of FW and CD (FWCD) were used. Further kinetic evaluation was performed to identify mixing’s effect on kinetic parameters and correlation of the kinetic parameters with digester performance (volatile solid removal (VS%) and specific methane production (SMP)). The four models applied were: modified Gompertz, logistic, first-order, and Monod. It was found that the CM mode revealed higher values of Rm and k as compared to the WM mode, and the trend was consistently observed in the modified Gompertz model. Nonetheless, the logistic model demonstrated good correlation of kinetic parameters with VS% and SMP. In the continuous systems, the optimum OLR was recorded at 4, 5, and 7 g VS/L/d for FW, CD, and FWCD respectively. Therefore, it was deduced that codigestion significantly improved digester performance. Electrical energy generation at the laboratory scale was 0.002, 0.003, and 0.006 kWh for the FW, CD, and FWCD substrates, respectively. Thus, projected electrical energy generation at the on-farm scale was 372 kWh, 382 kWh, and 518 kWh per day, respectively. Hence, the output could be used as a precursor for large-scale digester-system optimization.

This study highlighted the influence of molasses residue (MR) on the anaerobic treatment of cow manure (CM) at various organic loading and mixing ratios of these two substrates. Further investigation was conducted on a model-fitting comparison between a kinetic study and an artificial neural network (ANN) using biomethane potential (BMP) test data. A continuous stirred tank reactor (CSTR) and an anaerobic filter with a perforated membrane (AF) were fed with similar substrate at the organic loading rates of (OLR) 1 to OLR 7 g/L/day. Following the inhibition signs at OLR 7 (50:50 mixing ratio), 30:70 and 70:30 ratios were applied. Both the CSTR and the AF with the co-digestion substrate (CM + MR) successfully enhanced the performance, where the CSTR resulted in higher biogas production (29 L/d), SMP (1.24 LCH₄/gVS_added), and VS removal (>80%) at the optimum OLR 5 g/L/day. Likewise, the AF showed an increment of 69% for biogas production at OLR 4 g/L/day. The modified Gompertz (MG), logistic (LG), and first order (FO) were the applied kinetic models. Meanwhile, two sets of ANN models were developed, using feedforward back propagation. The FO model provided the best fit with Root Mean Square Error (RMSE) (57.204) and correlation coefficient (R²) 0.94035. Moreover, implementing the ANN algorithms resulted in 0.164 and 0.97164 for RMSE and R², respectively. This reveals that the ANN model exhibited higher predictive accuracy, and was proven as a more robust system to control the performance and to function as a precursor in commercial applications as compared to the kinetic models. The highest projection electrical energy produced from the on-farm scale (OFS) for the AF and the CSTR was 101 kWh and 425 kWh, respectively. This investigation indicates the high potential of MR as the most suitable co-substrate in CM treatment for the enhancement of energy production and the betterment of waste management in a large-scale application.