4.6 Article

Optimization of Flavonoid Extraction from Red and Brown Rice Bran and Evaluation of the Antioxidant Properties

Journal

MOLECULES
Volume 23, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/molecules23081863

Keywords

central composite design; response surface methodology; rice bran; flavonoids; antioxidant activity

Funding

  1. Research Management Centre (RMC), Universiti Putra Malaysia

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Recently, the quality-by-design concept has been widely implemented in the optimization of pharmaceutical processes to improve batch-to-batch consistency. As flavonoid compounds in pigmented rice bran may provide natural antioxidants, extraction of flavonoid components from red and brown rice bran was optimized using central composite design (CCD) and response surface methodology (RSM). Among the solvents tested, ethanol was most efficient for extracting flavonoids from rice bran. The examined parameters were temperature, solvent percentage, extraction time, and solvent-to-solid ratio. The highest total flavonoid content (TFC) in red rice bran was predicted as 958.14 mg quercetin equivalents (QE)/100 g dry matter (DM) at 58.5 degrees C, 71.5% (v/v), 36.2 min, and 7.94 mL/g, respectively, whereas the highest TFC in brown rice bran was predicted as 782.52 mg QE/100 g DM at 56.7 degrees C, 74.4% (v/v), 36.9 min, and 7.18 mL/g, respectively. Verification experiment results under these optimized conditions showed that the TFC values for red and brown rice bran were 962.38 and 788.21 mg QE/100 g DM, respectively. No significant differences were observed between the predicted and experimental TFC values, indicating that the developed models are accurate. Analysis of the extracts showed that apigenin and p-coumaric acid are abundant in red and brown rice bran. Further, red rice bran with its higher flavonoid content exhibited higher nitric oxide and 2,2-diphenyl-1-picrylhydrazyl scavenging activities (EC50 values of 41.3 and 33.6 mu g/mL, respectively) than brown rice bran. In this study, an extraction process for flavonoid compounds from red and brown rice bran was successfully optimized. The accuracy of the developed models indicated that the approach is applicable to larger-scale extraction processes.

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