Red wine quality is determined greatly by phenolic substances whose presence relies on extraction of grape skins and seeds during fermentation. Monitoring phenolic behaviour is beneficial for fermentation management because of the importance of maceration during red winemaking and its influence on phenolics that contribute to predominant red wine characteristics, such as colour, flavour and mouthfeel. Properly quantifying the kinetics associated, however, with red grape and wine phenolics is an intricate process. This review focuses on the extraction and ensuing reactions of principal phenolic substances during various stages of red winemaking as described by dynamic and spatial mathematical models. The extraction and reaction phenomena are concurrently influenced by several environmental and technological factors during fermentation, such as temperature, oxidation and mixing regimes, resulting in complex phenolic behaviour over time. As such, employing mathematical modelling is extremely useful for ascertaining the kinetic and spatial basis for phenolic behaviour, and the models significantly enhance the existing understanding of the extraction and reaction mechanisms of phenolic substances that are critical to red wine quality. Ultimately, this knowledge will allow for the development of predictive tools for phenolic extraction based on fruit composition and can potentially contribute to increased wine quality with optimised and sustainable production practices.

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数学建模以提高酿酒效率：红酒颜色和多酚提取与演化的回顾

红酒的质量很大程度上取决于酚类物质，酚类物质的存在取决于发酵过程中葡萄皮和种子的提取。监测酚的行为对发酵管理非常有益，因为在红酒酿造过程中浸渍的重要性及其对酚的影响，酚对红酒的主要特征（如颜色，风味和口感）有贡献。正确定量与红葡萄和葡萄酒中的酚类物质相关的动力学过程是一个复杂的过程。如动态和空间数学模型所述，本综述着重于红酒酿制各个阶段中主要酚类物质的提取和后续反应。在发酵过程中，萃取和反应现象同时受到多种环境和技术因素的影响，例如温度，氧化和混合方式，随着时间的推移会导致复杂的酚行为。因此，采用数学模型对于确定酚类行为的动力学和空间基础极为有用，并且这些模型显着增强了对酚类物质的提取和反应机理的现有理解，而酚类物质对红葡萄酒的质量至关重要。最终，这些知识将允许开发基于水果成分的酚类提取的预测工具，并可能通过优化和可持续的生产实践来提高葡萄酒质量。采用数学模型对于确定酚类行为的动力学和空间基础极为有用，并且这些模型显着增强了对酚类物质的提取和反应机理的现有理解，而酚类物质对红酒的质量至关重要。最终，这些知识将允许开发基于水果成分的酚类提取的预测工具，并可能通过优化和可持续的生产实践来提高葡萄酒质量。采用数学模型对于确定酚类行为的动力学和空间基础极为有用，并且这些模型显着增强了对酚类物质的提取和反应机理的现有理解，而酚类物质对红酒的质量至关重要。最终，这些知识将允许开发基于水果成分的酚类提取的预测工具，并可能通过优化和可持续的生产实践来提高葡萄酒质量。