果蔬中抗氧化剂协同作用的预测建模:功能性食品设计的多目标优化方法
Xia Wang1, Shiyu Zou1, Hongan Li1
1State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, Jiangxi, China.
Food chemistry
|August 23, 2025
概括
这项研究开发了一个计算框架,以确定最佳的水果和蔬菜组合,以获得增强的抗氧化功效. 该系统预测了协同作用的植物化学相互作用,有助于设计更健康的功能性食品.
科学领域:
- 营养科学
- 计算生物学
- 食品化学
背景情况:
- 水果和蔬菜中的植物化学物质通过复杂的相互作用提供抗氧化作用.
- 了解这些相互作用对于开发有效的功能性食品至关重要.
研究的目的:
- 引入一个多目标的优化框架来预测最佳的功能性食品组合.
- 利用计算方法设计富含抗氧化剂的产品配对.
主要方法:
- 在使用DPPH和ABTS测试的9个比率中评估了12种关键植物化学物质.
- 开发了一个基于Python的预测系统,以最小化EC50值并推断最佳配对.
- 根据实验数据验证模型,评估相关系数和p值.
主要成果:
- 在植物化学物质 (例如β-胡卜素/甲) 之间确定了依赖比率的协同作用和对抗作用.
- DPPH模型显示出显著的预测准确性 (r = - 0.69, p = 0.04).
- 在ABTS模型中,相关性较弱 (r = -0.55, p = 0.13),表明需要改进的领域.
结论:
- 开发的框架为设计富含抗氧化剂的食物组合提供了强大的数据驱动方法.
- 这种方法可以减少实验负担,并提供基于证据的饮食建议.
- 这些发现支持通过优化功能性食品提高公共健康.
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