Design and Employing of a Non-Linear Response Surface Model to Predict the Microbial Loads in Anaerobic Digestion of Cow Manure: Batch Balloon Digester

Abstract

Biogas is among the sources of renewable energy with a great potential to mitigate global energy challenges by virtue of the ease of implementation of the technology. The study focused on monitoring the total viable bacteria counts with the number of days, daily average ambient temperature and pH from a balloon type biodigester fed with 2500 L of cow manure (500 L of slurry each day for five successive days) with six months retention time using data acquisition system, standard methods and mathematical model. A non-linear response surface model was developed to predict the total viable bacteria counts with the predictors. The predictors were ranked by weights of importance to the desired targets by reliefF test. At the end of the anaerobic digestion cycle the cumulative volume of biogas was 6.75 m3 with 65.8% methane and 31.2% carbon dioxide. The ranking by weights of the predictors revealed that all the input parameters were primary factors and number of days contributed the most. Based on the testing data set, the response surface model was capable of predicting the total viable bacteria counts with high accuracy as the determination coefficient, root mean square error and p-value were 0.959, 0.197 and 0.602.