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Updated: Feb 23, 2026

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机器学习驱动的风味学:解读存储婴儿配方奶粉中特定阶段的挥发性化合物动态和感官恶化
Jianfeng Wang1, Mengyuan Yang1, Yanmei Xi1
1Key Laboratory of Geriatric Nutrition and Health, Ministry of Education, Beijing Technology & Business University, Beijing 100048, China.
Food chemistry
|February 21, 2026
概括
婴儿配方奶粉质量因脂质氧化而降低,产生异味. 机器学习模型准确地预测了这种感官衰退,使婴儿配方奶粉的保质期优化成为可能.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 计算生物学 计算生物学
背景情况:
- 婴儿配方奶粉 (IF) 对于婴儿营养至关重要.
- 储存导致感官恶化,影响消费者接受.
- 了解IF降解机制对于质量控制至关重要.
研究的目的:
- 调查IF的特定阶段的感觉恶化.
- 识别在储存期间导致风味丧失的机制.
- 开发用于IF保质期优化的预测模型.
主要方法:
- 风味学和脂肪酸分析.
- 定量描述性分析 (QDA). 定量描述性分析 (QDA).
- 机器学习 (随机森林,XGBoost).
主要成果:
- 六个属性被确定为IF质量损失的关键驱动因素.
- 化物和类被确定为主要的淡味标记物.
- 多不和脂肪酸的降解与淡味的产生相关.
结论:
- 脂质氧化是IF风味恶化的主要机制.
- 预测模型准确地将脂肪酸氧化与感官衰退联系起来.
- 开发了一个数据驱动的工具来优化IF的保质期.
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