Chemical composition and antimicrobial activity of essential oil of peppermint (Mentha piperita L.) grown in malatya

In this study, it was investigated that the drying kinetics of Mentha piperita leaves grown under the ecological conditions of Malatya province were dried in the shade and in the oven. The obtained data were fitted to nine different thin-layer drying models, and it was determined that the Midilli model was the best fit. An artificial neural network drying model with a three-layer feed-forward back propagation network structure was also developed. The developed artificial neural network model produced much better results than all other models used in this study. The values peculiar to dried peppermint samples such as moisture content, moisture rate, drying rate, drying time, effective diffusion coefficient and activation energy were determined. The essential oil was obtained from peppermint samples by water distillation method. The effect of the drying method on the essential oil composition was investigated, experiments were carried out according to the menthol content, which is the main component, and it was observed that the menthol content of the essential oil obtained from the samples dried in the shade had the highest percentage. The highest menthol ratio in essential oils obtained after the harvest in August, October and November 2019 was obtained from the harvest samples made in November. As a result of the GC–MS analysis of the samples obtained after the second harvest, it was determined that the menthol ratio of the second harvest samples was higher than the first harvest samples. The antimicrobial activity of essential oil was investigated, and it was determined that the effect of essential oil on gram-positive and gram-negative bacteria was at different levels. Keywords: Mentha piperita, essential oils, thin layer drying, hydrodistillation, GC-MS, ANN, antimicrobial activity.