应用神经网络优化芒果果汁的酶解工艺

尚朝杰; 王维民; 谌素华; 张晓迪; 刘艳春

doi:10.13386/j.issn1002-0306.2014.19.042

应用神经网络优化芒果果汁的酶解工艺

广东海洋大学食品科技学院

基金项目:

广东省科技计划项目(2012NL036)；

详细信息

作者简介:
尚朝杰 (1988-) , 男, 在读硕士, 研究方向:农产品加工及高效利用。;

王维民 (1958-) , 男, 教授, 研究方向:食品加工与贮藏。;

中图分类号: TS255.44;TP183
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出版历程
- 收稿日期: 2014-03-17

Optimization of mango juice enzymolysis process by neural network

College of Food Science and Technology, Guangdong Ocean University

摘要

摘要: 为研究酶解条件对芒果果汁得率的影响,在单因素的基础上建立了芒果果汁酶解工艺的神经网络模型,并对其工艺参数进行了优化。研究结果表明:果胶酶用量0.007%、纤维素酶用量0.001%、酶解温度40.6℃、酶解时间60min为最佳酶解工艺参数。此时芒果带皮果汁得率为80.48%,去皮果汁得率为66.47%,提高14.01%,且带皮果汁品质变化较小,可以接受。本研究为芒果果汁生产工艺改进提供参考。
- 神经网络 /
- 酶解 /
- 得率 /
- 果汁
Abstract: In order to study the influence of enzymatic hydrolysis conditions on mango juice yield, the neural network model of mango juice enzymolysis process was established on the basis of single factors, and the process parameters were optimized.The results showed that the optimal enzymolysis process parameters were as follows, pectinase dosage 0.007%, cellulase dosage 0.001%, reaction temperature 40.6℃ and time 60 min. Under these conditions, the yield of mango pulp with peel was 80.48%, the yield of mango pulp without peel was 66.47%, increased by 14.01%, and the quality of juice can be accepted with small changes.This study provides a reference for mango juice production process improvement.
- neural network /
- enzymolysis /
- yield /
- juice

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参考文献(18)

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