OPTIMIZATION OF ANTIOXIDANT EXTRACTION FROM KALUMPIT (TERMINALIA MICROCARPA DECNE) FRUITS

Authors

  • Dennis Marvin Opeña Santiago University of the Philippines Los Baños, College of Agriculture and Food Science, Institute of Food Science and Technology
  • Claire Solis Zubia University of the Philippine Los Baños, College of Agriculture and Food Science, Institute of Food Science and Technology
  • Sheba Mae Duque University of the Philippine Los Baños, College of Agriculture and Food Science, Institute of Food Science and Technology
  • Shekayna Eunice Pacia University of the Philippine Los Baños, College of Agriculture and Food Science, Institute of Food Science and Technology

DOI:

https://doi.org/10.15414/jmbfs.2020.10.2.301-309

Keywords:

Solvent extraction, 2-level factorial design, Box-Behnken design, DPPH scavenging activity, ABTS scavenging activity

Abstract

The effects of extraction parameters, including temperature (25 – 80 °C), time (30 – 90 min), solvent to sample (S/S) ratio (10 – 50 mL g-1), initial pH (3 - 8) and ethanol concentration (20 – 100%), on the % 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity of kalumpit were screened and optimized using 2-level factorial design and Box-Behnken design (BBD) of experiments. Temperature, S/S ratio, and ethanol concentration exhibited significant effects on the % DPPH radical scavenging activity of kalumpit extract. Response surface models developed for % DPPH and 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging activities of kalumpit fruit extract adequately fit and were used to determine the optimum extraction conditions. A desirability function approach determined the optimum conditions for solvent extraction of antioxidants at 80.0 °C, 10 mL g-1 S/S, and 51.66% ethanol concentration. This resulted in a maximum desirability value of 0.977 and predicted % DPPH and ABTS radical scavenging activities of 66.63 and 82.14, respectively. Validation of the adequacy of the predictive models showed no significant difference between experimental data and predicted values (p > 0.05), indicating that the models developed were adequate in describing the relationship between factors and responses.

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Published

2020-10-16

Issue

Section

Food Sciences