Kinetic Modeling and Parameters Identification Based on Metaheuristic Optimization Techniques for Extraction Process of Marrubium vulgare L. Essential Oil

Recently, increasing attention has been directed to the isolation of natural active components from various medicinal plants. In the present research, the extraction of essential oil from horehound (M. vulgare L.) is presented. Effects of mass ratio and particle size on the process performance were studied and kinetics were determined. The chemical composition of the volatiles present in M. vulgare L. was evaluated for the sample extracted in the optimum conditions (mass ratio, 3 kg m^-3 and particle size,0.1 d 0.63 mm) by using GC–MS. Eugenol (21.5%), -Caryophyllene (11.5%) and - bisabolene (10.3 %) were the major constituents found. Experimental data were fitted into three mathematical models having one and two time constants, in order to describe the extraction behaviour. The obtained coefficients of correlation show that the predicted and experimental data were in good agreement (0.9954 R 0.9982). In all cases the model constants have been found to change with mass ratio and particle size. The study was also an opportunity to improve the performance of two evolutionary algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), for identification of kinetic parameters with a satisfactory accuracy. The presented approach can be helpful for modeling and optimization of further extraction processes.