Optimization of Oil Recovery from Japonica Luna Rice Bran by Supercritical Carbon Dioxide Applying Design of Experiments: Characterization of the Oil and Mass Transfer Modeling

Abstract

This study presents an optimization strategy for recovery of oil from Japonica Luna rice bran using supercritical carbon dioxide (scCO2), based on design of experiments (DoE). Initially, a 24−1 two level fractional factorial design (FFD) was used, and pressure, temperature, and scCO2 flow rate were determined as the significant variables; while the yield, total flavonoids content (TFC), and total polyphenols content (TPC) were the response functions used to analyze the quality of the extracts recovered. Subsequently, central composite design (CCD) was applied to examine the effects of the significant variables on the responses and create quadratic surfaces that optimize the latter. The following values of pressure = 34.35 MPa, temperature = 339.5 K, and scCO2 flow rate = 1.8 × 10−3 kg/min were found to simultaneously optimize the yield (6.83%), TPC (61.28 μmol GAE/g ext), and TFC (1696.8 μmol EC/g ext). The fatty acid profile of the oils was characterized by GC-FID. It was demonstrated that the acids in largest quantities are C16:0 (15–16%), C18:1 (41%), and C18:2 (38–39%). Finally, three mass transfer models were applied to determine the mass transfer coefficients and assess the cumulative extraction curves, with an AAD% of 4.16, for the best model.