Screens of antioxidant activity (AA) of various natural products have been a focus of the research community worldwide. This work aimed to differentiate selected samples of Merlot wines originated from Montenegro, with regard to phenolic profile and antioxidant capacity studied by survival rate, total sulfhydryl groups and activities of glutathione peroxidase (GPx), glutathione reductase and catalase in H₂O₂⁻stressed Saccharomyces cerevisiae cells. In this study, DPPH assay was also performed. Higher total phenolic content leads to an enhanced AA under both conditions. The same trend was observed for catechin and gallic acid, the most abundant phenolics in the examined wine samples. Finally, the findings of an Artificial Neural Network (ANN) model were in a good agreement (r² = 0.978) with the experimental data. All tested samples exhibited a protective effect in H₂O₂⁻stressed yeast cells. Pre-treatment with examined wines increased survival in H₂O₂⁻stressed cells and shifted antioxidative defense towards GPx⁻mediated defense. Finally, sensitivity analysis of obtained ANN model highlights the complexity of the impact that variations in the concentrations of specific phenolic components have on the antioxidant defense system.
Keywords: Saccharomyces cerevisiae; antioxidant activity; artificial neural network; polyphenolics; red wine.