Application of RSM and Multivariate Statistics in Predicting Antioxidant Property of Ethanolic Extracts of Tea-Ginger Blend
Solomon Akinremi Makanjuola, Victor Ndigwe Enujiugha, Olufunmilayo Sade Omoba, David Morakinyo Sanni
European Journal of Medicinal Plants · pp. 200–211 · Published 22 Jan 2015
10.9734/EJMP/2015/15802Abstract
The optimum conditions for ethanolic extraction of antioxidants from tea-ginger blend were determined using response surface modelling. The relationship between the colour, hue index and antioxidant properties of the extracts were also expressed as multivariate models using ordinary least square, principal component and partial least square regressions (OLSR, PCR, and PLSR). Results from the multi-response optimisation revealed the optimum conditions for the extraction as temperature of 50.16°C, concentration of 2.1 g (100 ml)-1 and time of 5 minutes with a desirability of 0.68. The PLSR gave the most preferable model among the three multivariate regression techniques investigated. Hue index, A510 and a* were able to predict total flavonoid content (R2 = 0.933, Q2 = 0.905) and diphenyl-picrylhydrazyl (DPPH) radical activity (R2 = 0.945, Q2 = 0.919). The a*, A510, hue Index and hue were able to predict iron chelating activity (R2 = 0.854, Q2 = 0.794). The study revealed that colour and hue index property could give an indication of some antioxidant properties of ethanolic extracts of tea-ginger blend.
Cited by 6
Xiangyan Chen, Xia Zhao, Yanyun Gao · Marine Drugs · 2018
Solomon A. Makanjuola · Food Science & Nutrition · 2017
Solomon Akinremi Makanjuola, Victor Ndigwe Enujiugha, Olufunmilayo Sade Omoba · Food Science & Nutrition · 2015
Douglas Ongeri Ochora · Ginger - Cultivation and Use · 2023
Abhinav Jain, Beth Mason, Marianne Su-Ling Brooks · Polymers · 2025
Solomon A. Makanjuola, Victor N. Enujiugha, Olufunmilayo S. Omoba · Natural Product Communications · 2015
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