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来自不同地区的高温Daqu微生态歧视模型的构建

Liang Yang^1,2,3, Shuai Li⁴, Zijia Liu⁴

¹School of Brewing Engineering, Moutai Institute, Luban Ave, Renhuai 564507, Guizhou, China.

Food chemistry: X

|March 4, 2026

概括

中国的白 (Baijiu) 是一个

科学领域:

微生物学微生物学
发酵科学发酵科学
食品化学食品化学

背景情况:

中国白的独特区域风味与其造微生态有关.
高温达库是影响白特征的关键组成部分.

研究的目的:

调查中国白江地区地区区别的微生态驱动因素.
识别微生物和挥发性生物标志物用于质量控制和原产地识别.

主要方法:

来自六个地区的高温达库的多奥米克分析 (微生物和挥发性分析)
机器学习模型 (逻辑回归,神经网络) 用于区域歧视.
网络分析以了解微生物-风味化合物相互作用.

主要成果:

共享的核心微生物种群 (例如,Bacillus,Thermomyces) 具有特定区域的特征 (例如,四川的Kroppenstedtia,贵州的Oceanobacillus).
真菌群体反映了长期的区域差异,而细菌群体则对环境变化做出了反应.
挥发性分析确定了主要的代谢物,其中脂肪酸和酒精占主导地位. 贵州显示了最高的代谢物含量.
机器学习使用挥发性标记 (90%的准确度) 与微生物数据 (80%的准确度) 准确区分区域.
确定了18种微生物和20种挥发性生物标志物,区分了Baijiu的起源.

结论:

达库的微生物群落和挥发性化合物是Baijiu地区特征的关键决定因素.
挥发性生物标志物在准确的区域识别和质量控制方面比微生物数据更有效.
这项研究为理解和验证中国白江的不同区域特征提供了基础.

关键词:

歧视模式的模型.高温的达库高温的达库高温的达库机器学习机器学习微生态学微生态学地区地区地区地区地区

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