摘要
为了提高酿酒酵母发酵沙棘原汁的乙醇含量,该研究利用人工神经网络和正交试验相结合的方法,对酿酒酵母发酵沙棘原汁产乙醇工艺中的主要工艺参数发酵温度、基质的pH值、接种量和糖度进行了优化。试验结果表明,当发酵温度为28.5℃、pH值为3.7、接种量为0.18%、糖度为23%时,酿酒酵母发酵沙棘原汁产乙醇量最高,发酵液中的酒精度为14.0%vol。该研究提出了一种新的数据处理和分析方法,利用神经网络特有的自学能力,通过仿真、评估和优化,显著地提高了发酵液中的酒精度。
In order to increase the ethanol content in sea buckthom juice fermented by Saccharomyees cerevisiae, the fermentation conditions were optimized by the artificial neural network （ANN） and the orthogonal design. The optimal fermentation conditions were obtained as follows： fermentation temperature 28.5℃, pH value 3.7, inoculum 0.18% and sugar concentration 23%. Under these conditions, the ethanol content produced by S. cerevisiae fermentation in sea buckthom juice reached 14.0%vol. A novel method of data processing and analysis was put forward based on the ANN method, which can obviously increase the alcohol content through emulation, evaluation and optimization.
出处
《中国酿造》
CAS
北大核心
2011年第3期102-105,共4页
China Brewing
关键词
神经网络
酿酒酵母
发酵工艺
乙醇浓度
neural network
Saccharomyces cerevisiea., fermentation technology
ethanol content
