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超声波辅助酶法澄清树莓果汁的工艺优化
引用本文:师聪,李哲,张建萍,陈尚龙,巫永华,刘辉.超声波辅助酶法澄清树莓果汁的工艺优化[J].食品工业科技,2020,41(1):132-137.
作者姓名:师聪  李哲  张建萍  陈尚龙  巫永华  刘辉
作者单位:徐州工程学院, 江苏徐州 221018
基金项目:徐州工程学院青年项目(XKY2018249)。
摘    要:为了提高超声波辅助酶法制备树莓果汁出汁率和透光率,探讨了超声功率、超声时间、果胶酶用量、酶解时间和酶解温度对树莓果汁出汁率和透光率的影响。在单因素实验的基础上,采用Box-Behnken响应面试验设计,以树莓出汁率和透光率为响应值,运用期望函数同时优化多目标途径,优化了超声波辅助酶法制备树莓果汁的工艺条件。实验结果表明最优条件为:超声功率100 W,超声时间27 min,果胶酶添加量0.06%,酶解时间1.5 h,酶解温度44℃,在该条件下期望函数值最高为0.89,对应的树莓出汁率为84.05%,透光率为88.82%,验证实验结果与理论值相符,说明该模型实验回归性好,拟合度高。

关 键 词:树莓果汁    超声波辅助酶法    果胶酶    响应面法    期望函数    工艺优化
收稿时间:2019-04-12

Optimization of Ultrasonic Assisted Enzyme Method Clarification Technique on Raspberry Juice
SHI Cong,LI Zhe,ZHANG Jian-ping,CHEN Shang-long,WU Yong-hua,LIU Hui.Optimization of Ultrasonic Assisted Enzyme Method Clarification Technique on Raspberry Juice[J].Science and Technology of Food Industry,2020,41(1):132-137.
Authors:SHI Cong  LI Zhe  ZHANG Jian-ping  CHEN Shang-long  WU Yong-hua  LIU Hui
Affiliation:Xuzhou University of Technology, Xuzhou 221018, China
Abstract:In order to improve the juice yield and transmittance of raspberry juice prepared by ultrasonic synergistic pectinase,the effects of ultrasonic power,ultrasonic time,pectase dosage,enzymolysis time and enzymolysis temperature on the juice yield and transmittance of raspberry juice were investigated. Based on the results of single-factor experiment,the Box-Behnken design was used to optimize the ultrasonic synergistic pectinase of raspberry.The juice yield and transmittance of raspberry were also used as response values. The approach of desirability function optimized the multi-objective approach and optimized the technological conditions for the preparation of raspberry juice by ultrasonic synergistic pectinase method.The experiment results showed that:ultrasonic power 100 W,ultrasonic time 27 min,pectase 0.06%,enzymolysis time 1.5 h,enzymolysis temperature 44℃,The maximum value of this desirability function was 0.89 and the corresponding juice yield and transmittance of raspberry was 84.05% and 88.82%. The experimental data was consistent with the prediction model prediction.It accounted for that the model was well regressive and the degree of fitting of actual test was high.
Keywords:
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