响应面优化冷榨花生粕酶法制备多肽工艺的研究

Response Surface Methodology Optimization for Peptide Preparation from Cold Pressed Peanut Meal by Enzymatic Hydrolysis

运用了Min Run Equirelicated Res IV析因设计、爬陡坡试验以及中心复合响应面设计对碱性蛋白酶酶解冷榨花生粕蛋白制备活性多肽工艺进行了优化。析因设计结果和显著性分析发现,[E]和[S]为最重要因素(P<0.01),酶解pH和酶解时间为重要因素(P<0.05)。在析因设计、爬陡坡试验设计结果基础上应用中心复合响应面设计对[E](X1)、[S](X2)和酶解时间(X3)进行了响应面优化分析。响应面优化结果表明,在[E]=4 300 U/g[S],[S]=10.0%,酶解时间为85 min最优条件下,酶解液多肽含量达到最高,为(0.209±0.005)%(n=6),与模型预测值0.207 8%接近,偏差为5.77%。试验表明,酶促水解是制备活性多肽的有效方法。

In order to obtain the optimal processing parameters for the peptide preparation from cold pressed peanut meal, Min Run Equirelicated Res IV factorial design, the steepest ascent experiment and central composite design response surface methodology （CCD -RSM） were utilized. Factorial results and significant analysis has indi- cated that enzyme loading and substrate concentration were the most important factors at the 0.01 level （P 〈 0.01 ）, and hydrolysis pH and hydrolysis time were the key factors at the 0.05 level （P 〈 0.05 ）. CCD - RSM, based on the analysis of factorial analysis and the steepest ascent experiment, was adopted to evaluate the effects of three important independent variables, i.e. enzyme loading （ [ E ], X1 ）, substrate concentration （ [ S ], X2 ） and hydrolysis time （X3 ） on the dependent response （peptide Content, % ）. Polynomial regression model was formulated, and ANOVA was applied to determine significant parameters. The optimized parameters as suggested by the model （enzyme load- ing, 4 300 U/g[ S] ; substrate concentration, 10.0%, and hydrolysis time, 85min）, and the predicted peptide con- tent was of 0. 207 8%. The peptide content obtained experimentally was （0.209±0. 005 ） % （n = 6）, the bias was of 5.77%. The model was found to be in good agreement with the experimental data. Hence, alkaline proteinase hy- drolysis could turn out to be a potential and efficient aporoach to enhance and imorove Dentide yield.