通过统计建模来确定影响传统食品固态发酵的变量.
Guangyuan Jin1, Sjoerd Boeschoten2, Jos Hageman3
1The Lab of Brewing Microbiology and Applied Enzymology, School of Biotechnology, Jiangnan University, Wuxi 214122, China.
Foods (Basel, Switzerland)
|May 11, 2024
概括
统计模型显示,乳酸,而不是环境温度,可能在固态发酵过程中抑制了中国酒的产量. 需要进一步的研究来确认过程改进的关键变量.
科学领域:
- 生物技术是生物技术.
- 食品科学 食品科学 食品科学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 传统的固态发酵 (SSF) 过程往往缺乏科学依据,导致食品生产的不可预测结果.
- 数学模型难以捕捉SSF的动态复杂性,阻碍了影响产量和质量的关键因素的识别.
研究的目的:
- 开发统计模型,将工业数据与SSF中的最终中国酒精产量相关联.
- 确定影响中国传统酒精生产产量波动的关键变量.
主要方法:
- 使用工业数据建立的统计模型:初始粉,水,酸含量,初始温度和基质温度概况.
- 开发了一种乳酸抑制模型来解释季节性产量变化.
主要成果:
- 仅基于初始条件和温度配置文件的模型提供了不令人满意的产量预测.
- 季节性产量差异,特别是从4月到12月的下降,并不能通过环境温度来解释.
- 一个乳酸抑制模型表明,细菌产生的乳酸是降低产量的可能原因.
结论:
- 乳酸积累是SSF中限制中国酒精产量的可能因素.
- 综合微生物学和工程研究对于确定SSF优化关键变量至关重要.
- 这些发现为改善复杂的固态发酵过程提供了洞察力.
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