Optimization of critical parameters during antioxidants extraction from butterhead lettuce to simultaneously enhance polyphenols and antioxidant activity

VIACAVA GABRIELA ELENA; ROURA SARA INES; AGÜERO MARÍA VICTORIA

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

ELSEVIER SCIENCE BV

Lugar: Amsterdam; Año: 2015 vol. 146 p. 47 - 54

0169-7439

The present work was undertaken to optimize critical parameters (ethanol concentration, time and temperature) for antioxidant extraction from lettuce leaves, measured through DPPH radical scavenging activity (DRSA) and total phenolics content (TPC), using Response Surface Methodology (RSM). Individual optimization of each response was carried out and compared with a simultaneous optimization that allowed maximizing the two responses at the same time. For simultaneous optimization, Desirability function with the Larger-the-Best criteria was employed. Determination coefficients (R2) for the second-order models adjusted by RSM were above 91% and the models showed non-significant Lack of Fit. Single optimization of DRSA found conditions for extraction (70% ethanol, 32ºC and 2.5h) that allowed obtaining 69.62 mg ascorbic acid equivalent (AAE)/100g FW, while 43.20 mg gallic acid equivalents (GAE)/100g FW was predicted for TPC. Meanwhile, when optimizing only TPC as a single optimization, extraction conditions changed (70% ethanol, 42ºC and 2h) obtaining values of 46.92 mg GAE/100g FW for TPC and 65.43 mg AAE/100g FW for DRSA. Optimal conditions found when the Desirability function was applied to simultaneously enhance DRSA and TPC were: 70% ethanol, 32ºC and 2h. Under these conditions, good values for both responses were predicted: 69.62 mg AAE/100g FW and 44.37 mg GAE/100g FW for DRSA and TPC, respectively. These results were validated and a close agreement between experimental and predicted values indicated the suitability of the model employed and the success of RSM in modeling responses to characterize their dependence with extraction conditions under evaluation. Additionally, it was demonstrated the advantage of applying the Desirability function when more than one response must be optimized finding a compromise solution without harming any response as could happen when considering the optimal conditions for only one of them.