Optimization of Total Monomeric Anthocyanin (TMA) and Total Phenolic Content (TPC) Extractions from Red Cabbage (Brassica oleracea var. capitata f. rubra): Response Surface Methodology versus Artificial Neural Network

Abstract

Abstract: The aim of this study was to investigate the influence of solvent type, ultrasonic frequency, extraction time and temperature on the total phenolic content (TPC) and total monomeric anthocyanin (TMA) extraction from red cabbage (Brassica oleracea var. capitata f. rubra) using the response surface methodology (RSM) and artificial neural network. The red cabbage has been used as TPC and TMA sources due to its low cost and highly availability during all the year. The experimental data for the extraction of TPC and TMA were fitted to second-order polynomial models with higher regression coefficients than 0.902. The optimal conditions (in dry matter) for highest TPC extraction (7,049.5 mg gallic acid equivalent/kg) are: methanol as solvent, 3.60 kHz ultrasonic frequency at 67.6 °C for 59.6 min, while for TMA optimal extraction (0.3 mg/g) 2-propanol was used as solvent, 45 kHz ultrasonic frequency at 69.2 °C for 20.80 min. The artificial neural network (ANN) is better than RSM to predict the TPC and TMA extraction from red cabbage.