Optimization of the enzymatic esterification of diglycerol and lauric acid

In recent years, a number of industrial applications for lipases in biotransformation of fatty acids and lipids have been developed. One of the main reasons for this growing interest is the reduced overall catalyst cost owing to the development of commercially available immobilized enzymes, using polymeric carriers that facilitate recovery and reuse of the catalyst. Additional benefits for industrial applications include the specificity of the enzyme and the mild processing conditions. Diglycerol resulting from the dimerization of glycerol may replace molecules such as propylene glycol as the hydrophilic moiety of surfactants. Also, diglycerol fatty acid esters are useful as biodegradable nonionic surfactants for food, cosmetics, and pharmaceuticals. In this study, the enzymatic esterification of diglycerol and lauric acid has been optimized in a solvent-free system. The reaction was carried out in a stirred batch reactor with a vacuum pump in order to shift the equilibrium toward the products. The commercial lipase Novozym-435 was chosen as the most suitable catalyst, and the initial acid/alcohol ratio was always 1∶1. The reaction of lauric acid and diglycerol leveled off at equilibrium conversion after approximately 1 h of reaction. Previous work indicated that only temperature and catalyst concentration had significant effects on the conversion, and a full two-factorial design has proved effective in the study of the influence of these two variables on the process. The temperature range studied was 63–77°C, and the range of the catalyst concentration was 0.2–5.8 wt%. Both catalyst concentration and temperature were found to be significant factors in the esterification process, and their influences are positive. The effect of the interaction between temperature and catalyst concentration was small. A first-order approach could not fit the data adequately, and a model that included quadratic effects was required. A second-order model was developed to predict the yield of ester as a function of the variables. Analysis of residuals showed that the model predicted accurately the acid conversion over the experimental range considered. This model is useful to determine the optimal operating conditions for the industrial process. Presented in part at the 91st Annual Meeting of the AOCS in San Diego, April 2000.