Chemical structure components and antifungal activity of mint essential oil

Dragana V. Plavšić, Marija M. Škrinjar, Đorđe B. Psodorov, Lato L. Pezo, Ivan Lj. Milovanović, Dragan Đ. Psodorov, Predrag S. Kojić, Sunčica D. Kocić-Tanackov

Abstract


The objective of this research was to determine chemical compo­si­ti­on and to evaluate the antifungal activity of essential oil of Mentha piperita. By the application of GC/MS analysis of essential mint oil, 27 components were identified. The major components were menthol (39.9 %), menton (23.51 %), menthyl acetate (7.29 %), 1.8-cineol (5.96 %), iso-menton (5.24 %), iso-me­n­thol (3.17 %), trans-caryophyllene (2.88 %), limonene (2.14 %), pule­gon (1.38 %), beta-pinene (1.14 %) and piperiton (1.03 %). The quanti­ta­ti­ve structure–retention relationship (QSRR) was employed to predict the retention time (RT) of Menthapiperita essential oil compounds obtained in GC/MS analysis, using twelve molecular descriptors selected by genetic algorithm. The selected descriptors were used as inputs of an artificial neural network, to build an RT predictive QSRR model. The coefficient of determination was 0.983, during training cycle, indicating that this model could be used for prediction of RT values for essential oil compounds in Mentha piperita essential oil extracts. Essential oil of Mentha piperita showed antifungal activity on all tested isolates in the MIC range of 0.2–1.7 µl / ml and an MFC range of 1.7–454.5 µl / ml. The most powerful antifungal activity of mint was observed in C. cladosporioides of MFC value 1.7 µl / ml. P. aurantiogriseum showed the lowest sensitivity of MFC value 454.5 µl / ml.


Keywords


QSRR; ANN; genetic algorithm; antimicrobial potential

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DOI: https://doi.org/10.2298/JSC191210017P

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