Solubility prediction of mangosteen peel oil in Supercritical Carbon Dioxide using Neural Network

Natural compounds found in mangosteen peel such as squalene and α-cubebene were proven to exhibit antimicrobial, antibacterial and anticancer activity for cancer disease treatment. Supercritical Carbon Dioxide (SC-CO₂) extraction process was conducted at constant flowrate of 24 mL/min within 40 minutes and by varying temperature and pressure from 50 to 80°C and from 34.5 to 55.1 MPa, respectively. A multi-layer feedforward back-propagation Artificial Neural Network (ANN) model was developed for solubility prediction of mangosteen peel oil in SC-CO₂, where input variables were temperature and pressure. An optimal ANN model consisted of one hidden layer and five neurons was obtained with minimum value of Mean Square Error (MSE) i.e. 0.011 for 48 experimental data point used. The analysis showed that the ANN prediction model have a good correlation with the experimental data in which the values of correlation coefficient (R-value) for training, validating and testing obtained are 0.933, 0.982 and 0.927 proceedings.