分析和调节baijiu芳香活性化合物:整合代谢学,感官基因组学和人工智能
Wei Cheng1, Na Li1, Tianquan Pan1
1School of Biology and Food Engineering, Fuyang Normal University, Fuyang, Anhui 236037, China.
Food research international (Ottawa, Ont.)
|February 18, 2026
概括
这篇评论整合了代谢学,感官基因组学和人工智能 (AI) 来理解Baijiu的香味. 它提出了一个统一的框架,用于芳香化合物监管,质量控制和工业应用.
科学领域:
- 食品科学 食品科学 食品科学
- 生物技术是生物技术.
- 分析化学 分析化学
背景情况:
- 白香气受到通过复杂的生物和化学过程形成的微量化合物的影响.
- 之前的研究应用了代谢学,感官基因组学和人工智能单独,缺乏整合.
- 了解香味法规对于Baijiu的质量和工业的一致性至关重要.
研究的目的:
- 为Baijiu香味研究提供一个整合性框架,将化学分析,感官相关性和数据驱动模型连接起来.
- 综合多平台代谢学,感官基因组学和用于香味分析的AI的最新进展.
- 确定方法上的局限性,并提出 Baijiu生产中智能芳香调节的前景.
主要方法:
- 在Baijiu芳香研究中审查和综合有关代谢学,感觉基因组学和AI的现有文献.
- 整合多平台代谢学,用于对芳香化合物的定量绘制.
- 感官基因组学的应用,将气味活动与感知联系起来,以及用于跨模式数据集成的AI.
主要成果:
- 多平台代谢学使关键芳香化合物的定量映射成为可能.
- 感官基因组学将气味活动值和相互作用效应与感知结果联系起来.
- 机器学习模型促进了数据集成,用于香味预测和流程优化.
结论:
- 代谢学,感官基因组学和人工智能的综合框架对于全面了解Baijiu香味至关重要.
- 方法上的挑战包括灵敏度,感官数据的变化,以及AI模型的概括性.
- 这种综合方法为 Baijiu 的智能芳香调节和工业应用提供了机械洞察力和实用视角.
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