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Optimization of enzyme-assisted improvement of polyphenols and free radical scavenging activity in red rice bran: A statistical and neural network-based approach.

Ashish, A. Prabhu and Jayadeep, A. (2017) Optimization of enzyme-assisted improvement of polyphenols and free radical scavenging activity in red rice bran: A statistical and neural network-based approach. Preparative Biochemistry and Biotechnology, 47 (4). pp. 397-405. ISSN 1082-6068

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Abstract

The current study is focused on optimizing the parameters involved in enzymatic processing of red rice bran for maximizing total polyphenol (TP) and free radical scavenging activity (FRSA). The sequential optimization strategies using central composite design (CCD) and artificial neural network (ANN) modeling linked with genetic algorithm (GA) was performed to study the effect of incubation time (60–90 min), xylanase concentration (5–10 mg/g), cellulase concentration (5–10 mg/g) on the response, i.e., total polyphenol and FRSA. The result showed that incubation time has a negative effect on the response, while the square effect of xylanase and cellulase showed positive effect on the response. A maximum TP of 2,761 mg ferulic acid Eq/100 g bran and FRSA of 778.4 mg Catechin Eq/100 g bran was achieved with incubation time (min) ¼ 60.491; xylanase (mg/g) ¼ 5.4633; cellulase (mg/g) ¼ 11.5825. Furthermore, ANN-GA-based optimization showed better predicting capabilities as compared to CCD.

Item Type: Article
Uncontrolled Keywords: Artificial neural network-genetic algorithm; free radical scavenging activity; polyphenols; response surface methodology; rice bran
Subjects: 600 Technology > 08 Food technology > 16 Nutritive value > 07 Waste utilization
600 Technology > 08 Food technology > 21 Cereals > 01 Rice
Divisions: Grain Science and Technology
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 04 Jul 2017 09:36
Last Modified: 04 Jul 2017 09:36
URI: http://ir.cftri.com/id/eprint/12748

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