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Optimization of Bioactive Compound’s Extraction Conditions from Beetroot by Means of Artificial Neural Networks (ANN) CIGR Journal
Guiné, Raquel P.F.; Mendes, Mateus; Gonçalves, Fernando.
The present work used Artificial Neural Network (ANN) models to correlate beetroot extraction conditions with total phenolic compounds (TPC), anthocyanins (ANT) and antioxidant activity (AOA). The input variables were extraction time, type of solvent, solvent volume/sample mass (VMR) and order of extraction. The ANN models produced showed very good accuracy (R > 94 %), being suitable for data mining using weight analysis techniques. The experiments involved variable conditions: solvents (Methanol, ethanol:water and acetone:water), extraction times (15 and 60 min), VMR (5, 10 and 20), order of extract (3 sequential extractions). The TPC were evaluated by the Folin-Ciocalteu method, ANT by the SO2 bleaching method and AOA following the ABTS method. The...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Food Science; Food Chemistry Phenolic compounds; Antioxidant activity.
Ano: 2019 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5449
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