Kinetics of solvent-free lipase-catalyzed glycerolysis of olive oil in surfactant system.

This work reports experimental data and kinetic modeling of solvent-free glycerolysis of olive oil using a commercial immobilized lipase (Novozym 435) in the presence of Triton X-100 surfactant for the production of monoacylglycerols (MAG) and diacylglycerols (DAG). The experiments were performed in batch mode evaluating the effects of temperature (30-70 degrees C), enzyme concentration (2.5-18 wt %), Triton X-100 concentration (10-20 wt %), and glycerol to oil molar ratio (3:1, 6:1, and 9:1). Experimental results showed that lipase-catalyzed solvent-free glycerolysis with the addition of Triton X-100 might be a potential alternative route to conventional organic solvent methods, as good conversions were obtained with relatively low enzyme concentrations (9 wt %) in short reaction times (240 min). The glycerolysis and hydrolysis parallel reactions were considered with rate constants estimated by minimizing a maximum likelihood function. A very satisfactory agreement between experimental data and model results was obtained, thus allowing a better understanding of the reaction kinetics.

Inulinase production in a batch bioreactor using agroindustrial residues as the substrate: experimental data and modeling.

The production of inulinase employing agroindustrial residues as the substrate is a good alternative to reduce production costs and to minimize the environmental impact of disposing these residues in the environment. This study focused on the use of a phenomenological model and an artificial neural network (ANN) to simulate the inulinase production during the batch cultivation of the yeast Kluyveromyces marxianus NRRL Y-7571, employing a medium containing agroindustrial residues such as molasses, corn steep liquor and yeast extract. It was concluded that due to the complexity of the medium composition it was rather difficult to use a phenomenological model with sufficient accuracy. For this reason, an alternative and more cost-effective methodology based on ANN was adopted. The predictive capacity of the ANN was superior to that of the phenomenological model, indicating that the neural network approach could be used as an alternative in the predictive modeling of complex batch cultivations.