摘要
发酵培养基优化已经成为现代发酵工业的研究热点。如今很多现代数学统计方法也已经广泛地应用于微生物发酵培养基的优化工作中,其中以正交试计、均匀设计、响应面优化设计、人工神经网络等最为常用。在实际优化工作中,可以根据不同的研究目的,选用不同的优化设计,以达到最佳的效果。文中对这些常用现代数学统计学方法在培养基优化中的特点进行了总结,并介绍了它们之间的区别以及在实际工作中如何对它们进行选用。
Optimization of fermentation medium is considered one of the research focuses in modern fermentation industry. Nowadays lots of statistical methods and optimization techniques have been widely applied in the fermentation medium optimization. Among them,orthogonal design, uniform design, response surface design and artificial neural networks are the most common methods. Depending on different research purposes, proper designs were selected to achieve the best results. This paper summarized a comprehensive description of characters of these common methods in fermentation medium optimization. Differences and relatedness among them are also discussed in terms of selection criteria for practical purpose.
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2010年第5期110-113,共4页
Food and Fermentation Industries
基金
黑龙江省科技厅重大攻关项目(GA07B401)
黑龙江省科技厅重大攻关项目(GB05B401)
哈尔滨市科技局攻关项目(2009AA3CN079)
博士后科研启动资助金
黑龙江大学实验室开放基金
关键词
培养基优化
正交设计
均匀设计
响应面设计
人工神经网络
culture medium optimization, orthogonal design, uniform design, response surface design, artificial neural networks
