Electrokinetic assisted anaerobic digestion of spent mushroom substrate supplemented with sugar mill wastewater for enhanced biogas production

Pankaj Kumar, Vinod Kumar, Jogendra Singh and Piyush Kumar

Renewable Energy, 2021, vol. 179, issue C, 418-426

Abstract: This study investigated electrokinetic assisted anaerobic digestion of spent mushroom substrate supplemented with sugar mill wastewater for enhanced biogas production. Response surface method and artificial neural network tools were used to optimize the reactor performance. Findings showed that the best reactor performance was achieved at a temperature of 34.52 °C, a direct electric current of 1.61 V, and sugar mill wastewater loading of 59.61%, while the highest observed biogas yield and methane contents were 10344 mL and 63.05%, respectively. Moreover, amongst the different control parameters, sugar mill wastewater loading showed the most significant (P < 0.001) effect on bioenergy recovery from spent mushroom substrate followed by temperature (P < 0.0298) and electric current (P < 0.1783). Besides this, the artificial neural network (feed-forward-backpropagation configuration with logistic function) simulated the biogas/methane production more efficiently as compared to the quadratic model of response surface method as revealed from R2 (<0.9979 and 0.9987), root means-square error (>117.588 and 97.253), and model efficiency (<0.998) tools. Thus, supplementation of sugar mill wastewater along with low-level direct electric current can be useful for enhanced bioenergy recovery from the spent mushroom substrate.

Keywords: Artificial neural network; Biogas; Electrokinetic; Response surface methodology; Sugar industry wastewater (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:179:y:2021:i:c:p:418-426

DOI: 10.1016/j.renene.2021.07.045

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