Application of RSM and Multivariate Statistics inPredicting Antioxidant Property of EthanolicExtracts of Tea-Ginger Blend

摘要

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.