Open AccessOptimization and prediction of antioxidant properties of a tea‐ginger extract
Author(s) -
Makanjuola Solomon Akinremi,
Enujiugha Victor Ndigwe,
Omoba Olufunmilayo Sade,
Sanni David Morakinyo
Publication year - 2015
Publication title -
food science and nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 27
ISSN - 2048-7177
DOI - 10.1002/fsn3.237
Subject(s) - dpph , abts , chemistry , antioxidant , partial least squares regression , food science , flavonoid , phenol , biochemistry , organic chemistry , mathematics , statistics
A response surface approach was used to investigate the effects of temperature, concentration, and time on the antioxidant properties (total flavonoid ( TF ), total phenol ( TP ), peroxide scavenging activity ( PS ), iron chelating activity ( IC ), DPPH radical‐scavenging ability ( DPPH ), ABTS assay ( ABTS )) of aqueous extract of tea‐ginger (2:1) powder. Color indices, pH , and redox potential of the tea‐ginger powder were also measured and used as independent variables for the prediction of antioxidant properties of the extract using ordinary least square ( OLSR ), principal component ( PCR ), and partial least square ( PLSR ) regression. The R 2 values for TP , TF , ABTS , and PS response surface models were 0.8873, 0.9639, 0.6485, and 0.5721, respectively. The OLSR , PCR , and PLSR were able to provide predictive models for DPPH , TP , and TF of the tea‐ginger extract ( P < 0.05). The PLSR gave the most parsimonious model with an R 2 of 0.851, 0.736, and 0.905 for DPPH , TP , and TF , respectively.