中国食品学报2012，Vol.12Issue(5)：88-94,7.
基于神经网络和遗传算法的醋酸发酵培养基优化
The Optimization of Fermentation Medium of Acetic Acid Bacteria Based on Neural Network and Genetic Algorithm
王莹 1栾天奇 2朴美子1
作者信息
- 1. 青岛农业大学食品科学与工程学院 山东青岛266109
- 2. 中国海洋大学食品科学与工程学院 山东青岛266003
- 折叠
摘要
Abstract
The fermentation medium of acetic acid bacteria is optimized in this paper. The optimum carbon and nitrogen sources is decided by orthogonal test, and the optimum concentration is obtained using neural network and genetic algorithm. The results of the experiment show that the optimum carbon and nitrogen sources are glucose and yeast extract; the optimal medium contents ate glucose 2.7% and yeast extract 3.1% and ethanol 10.6% and NaCl 0.11 g/100 mL. A contrast experiment is designed between the two optimal fermentation mediums obtained by GA and the orthogonal test and the original medium under the condition of inoculums 4% and temperature 30 ℃ and 120 rpm. Hie result indicates that the acidity of the optimal fermentation medium obtained by GA is increased by 31% than the original medium and 16% than the medium obtained by the orthogonal test. It can be show that using neural network and genetic algorithm have a remarkable superiority in medium optimization.关键词
醋酸菌/培养基/神经网络/遗传算法Key words
Acetic Acid Bacteria/ medium/ neural network/ genetic algorithm
引用本文复制引用
王莹,栾天奇,朴美子..基于神经网络和遗传算法的醋酸发酵培养基优化[J].中国食品学报,2012,12(5):88-94,7.
