Abstract

Essential oils (EOs) are aromatic oily liquids prepared from plant material. Many plants are rich in EOs, which usually consisted of different secondary metabolites such as terpenoids. The EOs or their components have been shown to exhibit antioxidant, antimicrobial, antiviral, antimycotic, antitoxigenic, antiparasitic and insecticidal properties, which is main reason for their ivenstigation. Coriander and sage essential oils, isolated by hydrodistillation, were analyzed using gas chromatography, differential scanning calorimetry and thermogravimetry techniques in order to correlate chemical composition and thermal behavior. Results showed that evaporation process of sage EO takes place in two steps, while coriander EO was evaporated in one step. The activation energy of the evaporation process of both EOs was in accordance to the evaporation enthalpy of dominant compounds in analyzed samples. The quantitative structure–retention relationship (QSRR) was employed to predict the retention time (RT) of essential oil compounds obtained by GC analysis, using five molecular descriptors selected by genetic algorithm. The selected descriptors were used as inputs of an artificial neural network (ANN), to build an RT predictive QSRR model. The coefficient of determination was 0.969, indicating that this model could be used for prediction of RT values for coriander and sage essential oil compounds.

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