Modelling and Optimization of Ultrasound-Assisted Extraction of Phenolic Compounds from Black Quinoa by Response Surface Methodology

Phenolic compounds are currently the most investigated class of functional components in quinoa. However, great variability in their content emerged, because of differences in sample intrinsic and extrinsic characteristics; processing-induced factors; as well as extraction procedures applied. This study aimed to optimize phenolic compound extraction conditions in black quinoa seeds by Response Surface Methodology. An ultrasound-assisted extraction was performed with two different mixtures; and the effect of time; temperature; and sample-to-solvent ratio on total phenolic content (TPC) was investigated. Data were fitted to a second-order polynomial model. Multiple regression analysis and analysis of variance were used to determine the fitness of the model and optimal conditions for TPC. Three-dimensional surface plots were generated from the mathematical models. TPC at optimal conditions was 280.25 +/- 3.94 mg of Gallic Acid Equivalent (GAE) 100 g(-1) dm upon extraction with aqueous methanol/acetone, and 236.37 +/- 5.26 mg GAE 100 g(-1) dm with aqueous ethanol mixture. The phenolic profile of extracts obtained at optimal conditions was also investigated by HPLC. The two extracting procedures did not show different specificities for phenolic compounds but differed in the extraction yield.