分析加工奶油奶酪模型中的挥发性化合物,用于预测"新鲜奶油"香味感知
Coline Caille1,2, Mariem Boukraâ1, Cécile Rannou1
1Oniris-UMR CNRS 6144 GEPEA-MA(PS)2/USC INRAE 1498 TRANSFORM, 44322 Nantes, France.
Molecules (Basel, Switzerland)
|October 28, 2023
概括
这项研究预测了使用挥发性有机化合物 (VOC) 的加工奶酪中的"新鲜奶油"气味. 机器学习模型确定了关键的VOC,如octa-3,5-dien-2-one,这对于理想的奶油奶酪风味概况至关重要.
科学领域:
- 食品科学与技术 食品科学与技术
- 感官科学 感官科学
- 分析化学 分析化学
背景情况:
- 加工食品中的口味感知是复杂的,涉及口味和挥发性化合物之间的相互作用.
- 使用挥发性有机化合物 (VOCs) 预测气味感知比气味感知更少被探索.
- 了解这些关系对于食品行业控制和提高产品质量至关重要.
研究的目的:
- 分析如何组成和加工影响感官感知和VOC释放在加工奶油奶酪.
- 为了开发预测模型的预测模型
主要方法:
- 使用不同的纹理剂 (κ-carrageenan,agar-agar),水平和加热时间创建了16个加工奶油奶酪模型.
- 59名消费者使用R-A-T-A测试来评估感官感知.
- 在口过程中释放的VOC被测量使用体外口器和HS-SPME-GC-(ToF) MS分析.
主要成果:
- 阿加尔-阿加尔模型展出了一个
结论:
- 回归树和随机森林是基于VOC档案预测奶酪香味的有效工具.
- 识别像octa-3,5-dien-2-one这样的关键VOC可以指导开发具有所需"新鲜奶油"芳香特征的加工奶酪.
- 这项研究为食品行业提供了宝贵的见解,以控制风味感知和优化产品开发.
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