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

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.