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以酱油为原料,在单因素试验基础上,选取VC浓度、反应温度、pH为自变量,以亚硝酸盐清除率为响应值,采用3因素3水平试验设计法,得到二次多项式回归方程预测模型,优化酱油中亚硝酸盐的清除条件。回归预测模型具有高度显著性,方程对试验拟合较好,可对酱油亚硝酸盐清除率进行分析和预测;响应面图表明,交互项对清除率影响不显著,与回归模型交互项P值的分析结果一致。VC清除酱油亚硝酸盐的最佳条件为VC浓度0.48μg·mL-1、反应温度46.08℃、pH 2.38。在最佳条件下,酱油亚硝酸盐清除率可达52.4%,实测值为53.7%,两者较接近,拟合性良好,表明Box-Benhnken中心组合试验设计原理结合响应面法,优化酱油亚硝酸盐清除降解条件可行。
Taking soy sauce as raw material, on the basis of single factor test, VC concentration, reaction temperature and pH were chosen as independent variables, nitrite clearance rate was used as response value, and 3-level-3 level experimental design method was used to predict quadratic polynomial regression equation Model to optimize nitrite removal conditions in soy sauce. Regression prediction model is highly significant, the equation fitted well to the experiment, which can be used to analyze and predict the removal rate of nitrite in soy sauce. The response surface map shows that the interaction term has no significant effect on the clearance rate, The same analysis results. The optimal conditions of VC removal of soy sauce were VC concentration 0.48μg · mL-1, reaction temperature 46.08 ℃, pH 2.38. Under the optimum conditions, the removal rate of soy sauce was up to 52.4% and the measured value was 53.7%, which were close to each other and the fitting was good, which indicated that the design principle of Box-Benhnken combined experimental design and response surface method Removal of nitrate degradation conditions feasible.