Modelling of Biogas Yield from Anaerobic Co-digestion of Food Waste and Animal Manure using Artificial Neural Networks

Ejiroghene Kelly Orhorhoro, Joel O. Oyejide


The anaerobic digestion process is a technology that recovers energy in form of biogas and nutrients from biodegradable waste streams in useable forms in the absence of oxygen. It is sustainable, renewable and a zero-carbon form of energy supply. In this research work, modelling of biogas yield from co-digestion of food waste and animal manure using artificial neural networks was carried out. An experimental three stage continuous anaerobic digestion plant was used to co-digest food waste and animal manure. The composition of food waste and animal manure used include fufu, eba, starch, rice, beans, yam, fish, meat, moi moi, pig and cow dung. The feedstock was ground into fine particles to increase its surface area, and then mixed with water in a ratio of 1:2. The actual biogas yield was compared to the predicted biogas yield using artificial neural networks model. The performance of the developed artificial neural networks model was validated, and the results obtained from the research work revealed the effectiveness of the model to predict biogas yield with a mean squared error (MSE) of best validation performance of 5.1115e-4. Also, the coefficient of determination (R2) values of the training set, the testing set, the validation set, and the all data set were found to be high and close to 1, the values being 0.97193, 0.96510, 0.98378 and 0.97229 respectively. The high values R2 demonstrates the appropriateness of the artificial neural networks model for accurate estimation of anaerobic co-digestion of food waste and animal manure.  Besides, there was a good correlation between the actual and the predicted values of biogas yields. Therefore, the artificial neural networks model learned the relation between the input to the anaerobic digestion plant and the output in the biogas stream very well, thus the correct prediction of biogas yield.


Anaerobic co-digestion; Animal manure; Artificial neural networks model; Biogas yield; Food waste.

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