Box-Behnken响应面优化冷榨花生粕酶解制备花生肽工艺

在单因素试验基础上应用Box-Behnken响应面优化技术对中性蛋白酶酶解冷榨花生粕蛋白质制备活性多肽工艺进行了响应面优化分析,建立了酶促水解二阶多项式非线性回归方程和数值模型并分析了酶解时间X_1、酶添加量X_2、酶解pHX_3以及底物浓度X_4对多肽制备的影响规律。响应面优化方案为酶解时间200 min,酶添加量0.081 g/mL,酶解pH 10.0和底物质量浓度0.083 g/mL。优化条件下验证试验结果为(0.135 6±0.001 4)%,与模型预测值0.137 7%接近,偏差为1.55%。研究表明,单因素试验与响应面优化联用可应用于冷榨花生粕酶促水解制备活性多肽工艺的优化分析。

Optimization of polypeptide preparation parameters from cold-pressed peanut meal by Box-Behnken response surface methodology

A Box-Behnken design response surface methodology (BBD-RSM), composed of four independent variables, namely hydrolysis time,X1, enzyme loading amount,X2, hydrolysis pH,X3 and substrate concentrations,X4,based on one-factor-at-a-time (OFAT) experiments was applied to optimize polypeptide preparation parameters from cold-pressed peanut meal (CPPM) by limited enzymatic hydrolysis with neutral proteinase, establishing a second-order polynomial nonlinear regression equation and mathematical model, and analyzing the influencing profiles of the above four independent variables on CPPM polypeptide preparation. The optimum conditions for preparing polypeptide were determined as follows: hydrolysis time 200 min, enzyme loading 0.081g/mL, hydrolysis pH 10.0 and substrate concentration 0.083g/mL. The confirmation experiments were carried out under the optimum conditions and the results of confirmative tests and model predicted value were of (0.135 6±0.0014) % and 0.137 7%, respectively. The deviation between the measured and predicted results was 1.55%.Research indicated that the combination of OFAT and BBD-RSM was proven to be an efficient approach for optimization analysis of polypeptide preparation from CPPM.