功能性食品创新的人工智能:生物活性增强和配方优化:一个准系统的审查
Nadia Alkalbani1,2, Leen Shahin1, Hiba Benzeghiba1
1Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, PO Box 27272, United Arab Emirates.
Food chemistry: X
|February 20, 2026
概括
人工智能 (AI) 通过预测抗氧化剂活性和识别化合物来增强功能性食品研究. 然而,人工智能应用需要更多的实验验证和实践使用的伦理考虑的整合.
科学领域:
- 食品科学 食品科学 食品科学
- 计算生物学 计算生物学
- 营养科学 营养科学
背景情况:
- 人工智能 (AI) 越来越多地被用于功能性食品研究.
- 对53项研究 (2015-2025) 进行了准系统性审查,以分析人工智能应用.
- 该评论侧重于人工智能在抗氧化食品开发,化合物发现,代谢学和消费者建模方面的作用.
研究的目的:
- 在功能性食品研究中合成当前的AI应用.
- 确定新兴方向和知识差距,特别是在抗氧化食品开发方面.
- 强调人工智能在食品科学中的方法集成的机会.
主要方法:
- 从2015-2025年对53项同行评审研究进行分析.
- 人工智能方法的分类,包括数据驱动的人工智能 (经典机器学习) 和深度学习.
- 检查人工智能在预测抗氧化剂活性,识别生物活性化合物,代谢数据分析和消费者建模方面的应用.
主要成果:
- 人工智能方法成功预测抗氧化剂活性并识别生物活性化合物.
- 机器学习有助于聚类代谢数据并优化食物属性.
- 目前的人工智能发现主要是计算 (in silico) 的,实验验证有限.
- 消费者建模在很大程度上是预测性的,缺乏道德/监管整合.
结论:
- 人工智能在推进功能性食品研究方面显示出巨大的潜力,特别是在抗氧化剂开发方面.
- 人工智能驱动的预测有必要进行实验和临床验证.
- 食品和数据科学家之间的加强合作对于将AI见解转化为现实应用至关重要.
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