Investigating the Antioxidant Activity of Two Medicinal Plants; Thymus daenensis Čelak. And Echinophora cinerea (Boiss.) Hedge Lamond Essential Oils in Soybean Oil by Neuro-Fuzzy Modeling

The aim of this study was to evaluate the composition of essential oils from Thymus daenensis Čelak. and Echinophora cinerea (Boiss.) Hedge Lamond and predict oil oxidation using Neuro-Fuzzy modeling. In the hydrodistillation (HD) method, the starting time and total time for essential oil accumulation were 24 and 235 minutes, respectively. In the microwave-assisted hydrodistillation (MACE) method, these times were 8 and 58 minutes, respectively. The results indicated that the extraction yields of T. daenensis and E. cinerea using the HD and MACE methods were 2.26%, 2.34%, 1.18%, and 1.37%, respectively. For E. cinerea, the results were as follows. T. daenensis at a dosage of 500 mg/kg and E. cinerea at a dosage of 1000 mg/kg exhibited the most effective antioxidant activity. GC-Mass analysis results showed that thymol (39.8%) and p-cymene (19.2%) are the major compounds of T. daenensis, while α-phellandrene (16.6%), α-pinene (16.5%), p-cymene (15.8%), and thymol (13.3%) are the major compounds of E. cinerea’s essential oil. Prediction of antioxidant activity for T. daenensis and E. cinerea involved using a feedforward backpropagation network with a topology of 2-4-3 and 2-3-3 as the optimized models, respectively. Neuro-fuzzy modeling was a suitable approach for assessing soybean oil’s oxidation rate and evaluating essential oils’ antioxidant properties.