使用振动光谱学对油脂和食用油进行表征和分类,并与一类和多类化学测量方法一起使用
Ingrid A Moraes1, Marina G Neves2, Heinz W Siesler2
1Department of Food Engineering and Technology. School of Food Engineering. University of Campinas, SP, Brazil.
便携式光谱学可以根据油类型快速分类油. 具有化学测量的近红外 (NIR) 和拉曼装置可以准确地识别油中的日,大豆和橄油,提供一种非破坏性的质量控制方法.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 油脂凝在食品中提供了更健康的脂肪替代品.
- 油类型对油凝的特性和应用有很大的影响.
- 油的非破坏性,快速的质量评估至关重要.
研究的目的:
- 使用便携式光谱技术,根据油类别对油进行分类.
- 为了比较手持近红外 (NIR) 和便携式拉曼装置的疗效.
- 评估用于oleogel分析的多变量分类方法.
主要方法:
- 使用日,大豆和橄油与蜂制备油凝.
- 使用两个手持式NIR光谱仪和一个便携式拉曼装置获取光谱.
- 主要组件分析 (PCA) 的应用,数据驱动 - 类类类比的软独立建模 (DD-SIMCA) 和部分最小平方差异分析 (PLS-DA).
主要成果:
- 通过光谱方法,在按油类型分类油时,可以达到95%至100%的准确性.
- 无论是NIR还是拉曼光谱,再加上化学测量,都被证明有效.
- 该研究成功地将油类分类到oleogel矩阵中,这是一个尚未探索的领域.
结论:
- 便携式振动光谱和化学测量提供了一个有效的方法来分类oleogel.
- 这些技术提供了一种快速,非化学和可靠的质量控制方法.
- 该方法可能会扩展到其他食品矩阵的分类.
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