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中国精品科技期刊2020
Rudin改良法测定啤酒泡持性条件的优化[J]. 食品工业科技, 2013, (05): 218-222. DOI: 10.13386/j.issn1002-0306.2013.05.066
引用本文: Rudin改良法测定啤酒泡持性条件的优化[J]. 食品工业科技, 2013, (05): 218-222. DOI: 10.13386/j.issn1002-0306.2013.05.066
Optimization of conditions of a modified Rudin method to measure the foam stability using response surface methodology[J]. Science and Technology of Food Industry, 2013, (05): 218-222. DOI: 10.13386/j.issn1002-0306.2013.05.066
Citation: Optimization of conditions of a modified Rudin method to measure the foam stability using response surface methodology[J]. Science and Technology of Food Industry, 2013, (05): 218-222. DOI: 10.13386/j.issn1002-0306.2013.05.066

Rudin改良法测定啤酒泡持性条件的优化

Optimization of conditions of a modified Rudin method to measure the foam stability using response surface methodology

  • 摘要: 以Rudin改良法测定的啤酒泡持性为评价指标,在单因素和中心旋转组合实验设计结果的基础上,通过响应曲面法优化Rudin改良法测定啤酒泡持性的条件。结果显示:3个因素对泡持值测定的影响依次为气体总阀出口压力>CO2流量>待测样品预处理温度。分析结果显示,Rudin改良法测定啤酒泡持性的最优条件为气体总阀出口压力取0.3MPa,CO2流量取340mL/min,待测样品预处理温度取20℃,泡持值为110.813s,与预测值111.363s的相对误差为0.49%。回归方程的预测值和实验值差异不显著,所得回归模型拟合情况良好,可应用于实际操作。 

     

    Abstract: A central composite design was employed to optimize the conditions of a modified Rudin method to measure the foam stability with three factors:CO2 flow, gas outlet pressure of total valve, temperature of sample pretreatment. The combined effects of these variables on foam stability were investigated. Results showed that the generated regression models adequately explained the data variation and significantly represented the actual relationship between the independent variables and the responses. The results indicated that the effect order of three factors was as follows:gas outlet pressure of total valve, CO2 flow, and temperature of sample pretreatment. The canonical analysis revealed that the optimal conditions for measurement were:gas outlet pressure of total valve 0. 3MPa, CO2 flow 340mL/min, temperature of sample pretreatment 20℃. Under optimal conditions, the predicted value of foam stability was 111.363s, the testing value was 110.813s, and their relative error was 0.49%. The equation and the regression model were fitted well, and could be applied in practical experiment.

     

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