Phenomenological modeling of supercritical fluid extraction of oil from Elaeagnus angustifolia seeds

This research addressed the supercritical CO2 (sc-CO2) extraction of Elaeagnus angustifolia oil and its mathe-matical modeling. After experimental sc-CO2 extraction, the process was modeled based on mass transfer equations. Design of experiments and optimization were accomplished by Box-Behnken design to analyze the effects of the main operational parameters including pressure (20-30 MPa), temperature (313-333 K), and particle size (0.30-1.20 mm). Then, correlation of experimental extraction data with mathematical models was performed. The tunable parameters of the models were obtained by Genetic algorithm (GA) optimization. The model results were compared with experimental findings based on the average absolute relative deviation. The highest extraction yield (84.9% w/w) was achieved at the optimum conditions involving the pressure, tem-perature, and particle size of 30 MPa, 323 K, and 0.30 mm, respectively.The results obtained from the analysis of variance (ANOVA) indicated high and acceptable accuracy of mathematical models for the supercritical extraction process.

Automated summary

This research focused on the sc-CO2 extraction of Elaeagnus angustifolia oil and its mathematical modeling. Experimental extraction was followed by modeling the process using mass transfer equations. The effects of main operational parameters were analyzed using Box-Behnken design, and the models were optimized using Genetic algorithm. The highest extraction yield of 84.9% was achieved under the optimum conditions determined by the models. The results from ANOVA indicated the high accuracy of the mathematical models for the supercritical extraction process.