IntroductionPotato is one of the most valuable food crop grown in many countries [1]. It has been reported that, a considerable proportion of the potato cultivated globally consumed through starch processing which subsequently generates tons of wastewater that goes to pollute water bodies [1][2][3]. Wastewater of raw potato processed into starch are classified as complex wastewater [4,5], and its concentration of chemical oxygen demand (COD), total suspended solid (TSS) and volatile suspended solid of (VSS) can yield concentrations of 50000, 9700 and 9500 mg/L, respectively [6]. Arhoun et al. argued that recovering valuable resource such as bioenergy (biogas) from such wastewater to supplement energy needs will be beneficial to humans and society at large [6,7]. Anaerobic digestion has severally been reported as a successful bioprocess treating various organic wastewaters and subsequently generating biogas [7][8][9][10][11][12]. However, the biological mechanism of anaerobic digestion is not well understood due to the complexity of the bacterial community structure and bioconversion [13]. Hu et al. asserted that process modeling is a good tool for predicting and describing the performance of biological processes [13]. Other reports also confirmed that process modeling based on previously acquired data is one technical route to enhancing the performance of anaerobic processes. These process models are often developed [14,15]. Nonetheless, modeling of anaerobic digestion is quite challenging and tough because performance of anaerobic systems is complex and varies considerably with influent characteristics and operational conditions [16].Some predictive models have been developed in the past decades for biogas estimation during anaerobic treatment processes. For instance, a regression analysis model for estimating biogas generated in a landfill leachate treatment process was developed by Akaya et al.
AbstractHerein, a modeling approach to predict biogas yield within a mesophilic (35 ± 1°C) upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW) for pollutant removal was conducted. HRTs and seven anaerobic process-related parameters viz; chemical oxygen demand (COD), ammonium (NH 4 + ), alkalinity, total Kjeldahl Nitrogen, total phosphorus, volatile fatty acids (VFAs) and pH with average concentration of 4028.91, 110.09, 4944.67, 510.47, 45.20, 534.44 mg/L and 7.09, respectively, were used as input variables (x) to develop stochastic models for predicting biogas yield from the anaerobic digestion of PSPW. Based on the prediction accuracy of the models, it was established that, prediction of biogas yield from the UASB with the combination of COD, NH 4 + and HRT, or COD, NH 4 + , HRT and VFAs as input variables proved more efficient as opposed to HRT, alkalinity, total Kjeldahl Nitrogen, total phosphorus and pH. Highest coefficient of determination (R 2 ) observed was 97.29%, suggesting the efficiency of the models in making predictions. The developed models efficiencies co...
