Abstract:
Recently, increasing attention has been directed to
the isolation of natural active
components from various medicinal plants. In the pr
esent 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 studi
ed 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 ra
tio, 3 kg m
-3
and particle size,0.1<
d
<0.63 mm) by using GC–MS. Eugenol (21.5%),
β
-Caryophyllene (11.5%) and
β
-
bisabolene (10.3 %) were the major constituents fou
nd. Experimental data were fitted
into three mathematical models having one and two t
ime constants, in order to describe
the extraction behaviour. The obtained coefficients
of correlation show that the predicted
and experimental data were in good agreement (0.995
4<
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 ev
olutionary algorithms, Genetic
Algorithm (GA) and Particle Swarm Optimization (PSO
), for identification of kinetic
parameters with a satisfactory accuracy. The presen
ted approach can be helpful for
modeling and optimization of further extraction pro
cesses.
Keywords:
Genetic algorithm, Grinding effect, Parameter iden
tification, Particle swarm
optimization Mass ratio effect.
