基于神经网络算法的食用白醋发酵过程优化  

Optimization of Fermentation Process of Edible White Vinegar Based on Neural Network Algorithm

作　　者：胡惠娟[1] HU Hui-juan(Jiujiang Vocational University,Jiujiang 332000,China)

机构地区：[1]九江职业大学,江西九江332000

出　　处：《中国调味品》2020年第10期97-99,共3页China Condiment

基　　金：江西省教育厅科学技术研究项目(GJJ171244)。

摘　　要：以食用白醋的发酵过程条件为研究对象,以单影响因子对白醋发酵过程中醋酸度的影响数据和正交试验醋酸度检测数据为试验样本,建立白醋发酵条件和醋酸浓度之间的神经网络数据模型,对模型求解后得到白醋发酵条件的最佳组合方式。经过优化试验验证,预估白醋发酵醋酸度浓度与试验得到的醋酸浓度相对误差均值小于2.8%。利用神经网络进行白醋发酵过程优化,对白醋发酵优化结果的提高具有重要意义。In this paper,the fermentation conditions of edible white vinegar are taken as the research object.Take the influence data of single influencing factor on the degree of acetic acid of white vinegar in the fermentation process and the detection data of degree of acetic acid by orthogonal test as the test samples,the neural network data model between the fermentation conditions of white vinegar and the concentration of acetic acid is established.After solving the model,the best combination mode of white vinegar fermentation conditions is obtained.Through the verification optimized test,the relative error between the estimated acetic acid concentration of white vinegar and the acetic acid concentration obtained by the test is less than 2.8%.Using neural network to optimize the fermentation process of white vinegar is of great significance to improve the optimized results of white vinegar fermentation.

关 键 词：白醋发酵 醋酸度 神经网络 

分 类 号：TS264.22[轻工技术与工程—发酵工程]