基于挥发性有机化合物的预测模型,对葡萄酒中的烟雾污染进行预测
Cheng-En Tan1,2,3, Bishnu Prasad Neupane4, Yan Wen4
1Department of Computer Science, University of California, Davis, Davis, California 95616, United States.
Journal of agricultural and food chemistry
|March 27, 2024
概括
使用葡萄和葡萄酒挥发性有机化合物 (VOC) 数据,可以预测葡萄酒的烟雾污染. 这种数据驱动的方法可以在发酵前准确地识别受烟污染的葡萄酒,从而保持葡萄酒的质量.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
背景情况:
- 烟雾污染显著降低了葡萄酒的质量,这对葡萄酒行业构成了关键挑战.
- 挥发性有机化合物 (VOC) 是葡萄和葡萄酒中烟雾污染的关键指标.
研究的目的:
- 开发基于数据的模型,利用VOC度预测葡萄酒烟雾污染.
- 评估在发酵前葡萄和葡萄酒样本中预测烟雾污染的可行性.
主要方法:
- 在48个葡萄和56个葡萄酒样本中分析了20个VOCs.
- 应用单变量分析和预测建模,包括对VOC度的日志转换.
- 开发回归模型来预测烟雾污染指数,以及用于检测污染葡萄酒的分类模型.
主要成果:
- 使用葡萄和葡萄酒VOC的预测模型实现了高精度 (PCC = 0.82,R2 = 0.68).
- 仅使用葡萄VOCs的模型也显示出强大的预测能力 (PCC = 0.76,R2 = 0.56).
- 分类模型有效地检测到烟雾污染的葡萄酒,精度高 (0.92) 和F1分数 (0.82).
结论:
- 葡萄和葡萄酒中的VOC度可以准确预测烟雾污染水平.
- 这种预测能力允许在发酵前早期检测和管理烟雾污染.
- 该研究为葡萄酒行业的烟雾污染预测提供了数据驱动的框架和可访问的代码.
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