Optimization of flavonoid recovery in the extract of red and brown rice bran using response surface methodology

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 w...

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Bibliographic Details
Main Authors: Ghasemzadeh, Ali, Jaafar, Hawa Z. E., Baghdadi, Ali
Format: Conference or Workshop Item
Language:English
Published: Faculty of Agriculture, Universiti Putra Malaysia 2018
Online Access:http://psasir.upm.edu.my/id/eprint/77386/1/8TH%20IAC%20%E2%80%93%206TH%20ISFA%202018-64.pdf
http://psasir.upm.edu.my/id/eprint/77386/
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Summary: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). 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 °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 °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. Analysis of the extracts showed that apigenin and p-coumaric acid are abundant in red and 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.