Optimization of nutrient medium composition for the production of lipase from waste cooking oil using response surface methodology and artificial neural networks

Abstract

Lipases are a class of triacylglycerol hydrolases which have found a lot of applications as a result of their unique characteristics such as stability, specificity, economic attractiveness etc. This study examined the effect of some microbial stimulants (olive oil, MgSO4 and KH2PO4) on the production of lipase from waste cooking oil (WCO). The fermentation experiments were planned using a three-variable Box-Behnken design and the impact of the stimulants was optimized with response surface methodology (RSM) and artificial neural network (ANN). The results revealed that intermediate concentrations of olive oil, MgSO4 and KH2PO4 were needed to maximize lipase activity. The ANN model predicted an optimal lipase activity of 177.19 U/mL and this was obtained at olive oil, MgSO4 and KH2PO4 concentration of 0.58, 0.04 and 0.22 w/w% respectively while the RSM model predicted an optimal lipase activity of 176.52 U/mL at olive oil, MgSO4 and KH2PO4 concentration of 0.63, 0.05 and 0.25 w/w% respectively. The ANN model was superior to the RSM model in predicting lipase production and this was reflected by better statistical metrics. Thus, biological stimulants can facilitate the fermentation process for optimal lipase production from WCO.