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Muzolf-Panek M, Gliszczyńska-Świgło A. Extraction optimization for the antioxidants from Nigella sativa seeds using response surface methodology. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2022. [DOI: 10.1007/s11694-022-01575-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
AbstractAlthough many studies have explored the bioactive compound content of Nigella sativa (black seed – BS) essential oil, data on the phenolic compound content in the extracts of Nigella sativa seeds gives inconclusive results [1–3]. In this study, response surface methodology (RSM) with a central composite plan (CCP) was used for the experimental design and identification of the optimal conditions for maximizing the phenolic content and the antioxidant activity of BS extract. The independent variables were as followed: temperature (22.9–67.1ºC), time (31.7–208.2 min), and methanol concentration in water (5.9–94.1% v/v). Different response variables (total polyphenols – TPC, total flavonoids – TFC and the antioxidant activity – DPPH and TEAC) required different optimal conditions to maximize them. The multi-response optimization was performed to determine the extraction conditions, which would simultaneously ensure the highest phenolic content and the antioxidant activity. The optimal conditions derived from the multi-response desirability function were as followed: 120 min, 56 °C and 50% methanol, giving the TPC = 7.05 mg/g, TFC = 3.05 mg/g, DPPH = 9.04 µmol/g and TEAC = 33.24 µmol/g (with desirability function coefficient = 0.83). Solvent concentration was established as a crucial parameter for the extraction of antioxidants from BS. A quercetin derivative and two derivatives of kaempferol were determined by HPLC (high performance liquid chromatography) analysis of the BS extract at the optimal conditions. The accuracy of the models for all response variables was confirmed by a high correlation coefficient (r = 0.99) between the experimental values and those predicted under optimal conditions.
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