Potentiality of independent component regression in assessment of the peaks responsible for antimicrobial activity of Satureja hortensis L. and Oliveria decumbens Vent. using GC–MS

Abstract

Satureja hortensis L. and Oliveria decumbens Vent. are used in traditional medicine in the world due to its antifungal, antibacterial and antioxidant properties. In this study, the antimicrobial activities in Satureja hortensis L. and Oliveria decumbens Vent. essential oils against three microbial strains were evaluated by two different methods, including: disk diffusion method and micro-broth dilution assay [with minimal inhibitory concentration (MIC) between 0.025 and 0.500 µL/mL, and minimal lethal concentration (MLC) between 0.050 and 1.000 µL/mL] and qualitative analysis was performed by gas chromatography–mass spectrometry technique (GC–MS). The peaks potentially responsible for the antimicrobial activity in essential oils samples were indicated by some linear multivariate calibration techniques with different preprocessing methods. From the studied techniques, independent component regression (ICR) was preferred to exhibit the potential antimicrobial active compounds in Satureja hortensis L. and Oliveria decumbens Vent. essential oils because of its high repeatability, simplicity, and interpretability of the regression coefficients. Independent components (ICs) can give more chemical explanation than principal components (PCs), because independence is a high-order statistic that is a much stronger condition than orthogonality.