In this study, the classical method of one-variable at a time bioprocess design and Response Surface Methodology (RSM) was performed to evaluate the effects of aeration, agitation and temperature on phenol degradation by Pseudomonas fluorescence. Experiments were performed as a function of temperature (25-45°C), aeration (1.0-3.5 vvm) and agitation (200-600 rpm). The results of the one-variable at a time bioprocess design showed that percent phenol degradation increased with increased aeration, agitation and temperature up to a value of 3.0 vvm, 300 rpm and 30°C, respectively. Above these respective values, the percent phenol degradation decreased. Furthermore, phenol biodegradation was optimized by 23 full-factorial central composite design. Statistical analysis of results revealed that the linear and quadratic terms of these variables had significant effects and evident interactions existing between the temperature and agitation were found to contribute to the response at a significant level. More also, full-factorial central composite design used for the analysis of treatment combinations gave a second-order polynomial regression model, which was in good agreement with experimental results, with R2 = 0.9647 (p<0.05). By response surface methodology and multistage Monte- Carlo optimization technique, the optimal degradation (fermentation) parameters for enhanced phenol degradation were obtained. The optimum process conditions for maximizing phenol degradation (removal) were recognized as follows: temperature 30°C, aeration 3.0 vvm and agitation 300 rpm and the model predicted a maximum percent phenol degradation of 60.7% at these optimum process conditions. This confirmed the closeness of the model to the experimental result of 60.8%.
S.E. Agarry, B.O. Solomon and T.O.K. Audu, 2010. Optimization of Process Variables for the Batch Degradation of Phenol by Pseudomonas fluorescence Using Response Surface Methodology. International Journal of Chemical Technology, 2: 33-45.