基于BP神经网络和遗传算法的大米抗氧化肽酶解工艺优化

Optimization of Enzymatic Hydrolysis Process of Rice Antioxidant Peptides Based on BP Neural Network and Genetic Algorithm

以大米蛋白为原料,通过中性蛋白酶酶解制备大米抗氧化肽。以ABTS自由基清除率作为抗氧化性评价指标,在单因素试验结果的基础上,进行Box-Behnken响应面设计试验,并结合BP神经网络和遗传算法,旨在优化大米抗氧化肽的酶解制备工艺条件。结果表明:大米抗氧化肽最优酶解工艺为反应温度50℃,体系pH 8.2,料液比值17.65 g/100 mL,酶添加量4374 U/g。在此条件下,大米抗氧化肽ABTS自由基清除率为82.22%。

Rice protein was used as a raw material to prepare rice antioxidant peptides by enzymatic hydrolysis of neutral protease,and the antioxidant capacity was evaluated by ABTS free radical scavenging rate.On the basis of single-factor experiments,Box-Behnken design experiment was used to arrange the tests,combined with BP Neural network and genetic algorithm to optimize the enzymatic hydrolysis process.The results showed that the optimal enzymatic hydrolysis process was reaction temperature 50℃,system pH 8.2,feed-liquid ratio 17.65 g/100 mL and the amount of enzyme 4374 U/g.Under this condition,ABTS free radical scavenging rate of rice antioxidant peptide was 82.22%.