食品系统中人工智能支持的成分替代:感官,功能,营养和文化优化的审查和概念框架
1Department of Food Engineering, Faculty of Agriculture, Ataturk University, Erzurum 25240, Türkiye.
Foods (Basel, Switzerland)
|November 27, 2025
概括
人工智能 (AI) 为食品系统中的成分替代挑战提供了解决方案. 本综述提出了一个使用人工智能的框架来模拟味道,预测功能,描述营养素和过限制,以实现更好的食品创新.
科学领域:
- 食品科学 食品科学 食品科学
- 人工智能的人工智能
- 计算化学计算化学
背景情况:
- 配料替代是复杂的,需要同时考虑感官,功能,营养和调节因素.
- 现代食品系统在成分更换过程中面临着在保持真实性和性能方面的挑战.
研究的目的:
- 审查人工智能 (AI) 在解决成分替代挑战中的应用.
- 提出一个模块化框架,用于在关键科学领域实现人工智能的成分替代.
主要方法:
- 一个叙事评论,综合了Scopus,Web of Science和谷歌学者的文献.
- 文献选择侧重于基础食品科学和新兴的人工智能应用.
- 开发一个集成人工智能技术 (机器学习,GNN,NLP,优化) 与特定领域数据的模块化框架.
主要成果:
- 一个拟议的四个领域框架:风味/香味建模,功能性质预测,营养分析和基于约束的过.
- 将各种AI技术与诸如挥发性化合物库,学测量和监管本体学等数据集集集成.
- 确定关键的局限性,包括缺乏多式联运数据集,有限的模型可解释性,以及工作流集成的弱点.
结论:
- 人工智能为开发先进的成分替代系统提供了巨大的潜力.
- 解决数据,可解释性和整合差距对于现实世界的部署至关重要.
- 未来的方向包括为可持续和个性化的食品创新创建透明,可扩展和上下文意识的系统.
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