Recovery of Biologically Active Compounds from Stinging Nettle Leaves Part II: Processing of Exhausted Plant Material after Supercritical Fluid Extraction
Saša Đurović,
Lato Pezo,
Uroš Gašić,
Stanislava Gorjanović,
Ferenc Pastor,
Julia G. Bazarnova,
Yulia A. Smyatskaya,
Zoran Zeković
Affiliations
Saša Đurović
Laboratory of Chromatography, Institute of General and Physical Chemistry, Studentski trg 12/V, 11158 Belgrade, Serbia
Lato Pezo
Laboratory of Chromatography, Institute of General and Physical Chemistry, Studentski trg 12/V, 11158 Belgrade, Serbia
Uroš Gašić
Institute for Biological Research “Siniša Stanković”—National Institute of Republic of Serbia, University of Belgrade, Bulevar despota Stefana 142, 11060 Belgrade, Serbia
Stanislava Gorjanović
Laboratory of Chromatography, Institute of General and Physical Chemistry, Studentski trg 12/V, 11158 Belgrade, Serbia
Ferenc Pastor
Faculty of Chemistry, University of Belgrade, Studentski trg 12, 11000 Belgrade, Serbia
Julia G. Bazarnova
Graduate School of Biotechnology and Food Industries, Peter the Great Saint-Petersburg Polytechnic University, Polytechnicheskaya Street, 29, 195251 Saint-Petersburg, Russia
Yulia A. Smyatskaya
Graduate School of Biotechnology and Food Industries, Peter the Great Saint-Petersburg Polytechnic University, Polytechnicheskaya Street, 29, 195251 Saint-Petersburg, Russia
Zoran Zeković
Faculty of Technology, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
Stinging nettle (Urtica dioica L.) is one fantastic plant widely used in folk medicine, pharmacy, cosmetics, and food. This plant’s popularity may be explained by its chemical composition, containing a wide range of compounds significant for human health and diet. This study aimed to investigate extracts of exhausted stinging nettle leaves after supercritical fluid extraction obtained using ultrasound and microwave techniques. Extracts were analyzed to obtain insight into the chemical composition and biological activity. These extracts were shown to be more potent than those of previously untreated leaves. The principal component analysis was applied as a pattern recognition tool to visualize the antioxidant capacity and cytotoxic activity of extract obtained from exhausted stinging nettle leaves. An artificial neural network model is presented for the prediction of the antioxidant activity of samples according to polyphenolic profile data, showing a suitable anticipation property (the r2 value during the training cycle for output variables was 0.999).
