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中国精品科技期刊2020
马奇虎, 邵佩兰, 张海红, 周世平. 响应面法优化超声波辅助提取枣皮红色素[J]. 食品工业科技, 2014, (08): 255-259. DOI: 10.13386/j.issn1002-0306.2014.08.049
引用本文: 马奇虎, 邵佩兰, 张海红, 周世平. 响应面法优化超声波辅助提取枣皮红色素[J]. 食品工业科技, 2014, (08): 255-259. DOI: 10.13386/j.issn1002-0306.2014.08.049
MA Qi-hu, SHAO Pei-lan, ZHANG Hai-hong, ZHOU Shi-ping. Optimization of ultrasonic-assisted extraction of red pigment from jujube peel by response surface methodology[J]. Science and Technology of Food Industry, 2014, (08): 255-259. DOI: 10.13386/j.issn1002-0306.2014.08.049
Citation: MA Qi-hu, SHAO Pei-lan, ZHANG Hai-hong, ZHOU Shi-ping. Optimization of ultrasonic-assisted extraction of red pigment from jujube peel by response surface methodology[J]. Science and Technology of Food Industry, 2014, (08): 255-259. DOI: 10.13386/j.issn1002-0306.2014.08.049

响应面法优化超声波辅助提取枣皮红色素

Optimization of ultrasonic-assisted extraction of red pigment from jujube peel by response surface methodology

  • 摘要: 采用响应面法优化超声波辅助提取枣皮中红色素的条件。在单因素实验基础上,选择超声时间、超声波功率、NaOH浓度和液料比为提取因子,色素提取液吸光度值为响应值,进行四因素三水平Box-Behnken中心组合设计,采用响应面法分析优化提取工艺。超声波辅助提取枣皮中红色素的最优条件为:超声时间30min,超声功率80W,NaOH浓度0.5mol/L,料液比1∶10g/mL(w/v)。在此条件下,模型预测吸光度值为1.445,验证实验吸光度值为1.427,说明模型具有良好的拟合度,能较好的描述实验结果。 

     

    Abstract: The Ultrasonic-assisted extraction condition of red pigment from jujube peel was optimized by using response surface method. Based on single factor experiments, a four-factor-three-level experiment design were developed by box-benhnken central composite design method with the causal factors of ultrasonic time, ultrasonic power, concentration of NaOH, ratio of raw material to liquid and the extract absorbance value for the response, and the response surface methodology ( RSM) was applied to optimize the ultrasonic-assisted extraction. The optimum ultrasonic-assisted extraction conditions were as follow:ultrasonic time was 30min, ultrasonic power was 80W, concentration of NaOH was 0.5mol/L and the ratio of raw material to liquid was1∶10g/mL (w/v) . Under the optimum extraction technology condition, the absorbance value predicted of the model was 1.445 and the experimented value was 1.427. The model had a good degree of fitting, so it could be used to describe the test result preferably.

     

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