在便携式仪器上获得的拉曼空间分解指纹的可食用植物油的歧视/分类
Guillermo Jiménez-Hernández1, Fidel Ortega-Gavilán1,2, M Gracia Bagur-González1
1Department of Analytical Chemistry, Faculty of Science, University of Granada, C/Fuentenueva w/n, 18071 Granada, Spain.
Foods (Basel, Switzerland)
|January 23, 2024
概括
空间偏移拉曼光谱 (SORS) 为分析食用油提供了一种快速,环保的方法. 该技术通过分析它们的脂肪酸含量,有效地区分向日油和橄油,从而使原材料的识别成为可能.
科学领域:
- 分析化学 分析化学
- 食品科学 食品科学 食品科学
- 频谱学是一种光谱学.
背景情况:
- 食品行业越来越需要快速,经济高效,环保的分析方法.
- 与便携式仪器相结合的指纹技术正在获得食品分析的吸引力.
研究的目的:
- 评估空间偏移拉曼光谱学 (SORS) 的指纹识别和食用植物油分类能力.
- 评估SORS指纹的潜力,根据其成分来区分不同油类.
主要方法:
- 使用便携式空间偏移拉曼光谱 (SORS) 分析仪获得可食用植物油 (日油和橄油) 的光谱指纹.
- 应用无监督 (层次组件分析 - HCA,主要组件分析 - PCA) 和监督 (支持矢量机 - SVM,k-最近邻居 - kNN,无效平均值相似性 - SIMCA) 的模式识别技术进行数据分析.
- 专注于与自由脂肪酸含量相关的光谱区域,特别是油脂和酸.
主要成果:
- 索尔斯指纹,得到快速,没有样本预处理,有效地区分向日油和橄油.
- 模式识别分析显示,自由脂肪酸含量,特别是油脂和烯酸,显著影响了样品分类.
- 已建立的模型产生了可靠的质量参数,使得在石油生产中使用的原材料可以辨别.
结论:
- 空间偏移拉曼光谱 (SORS) 是一种多功能且有效的工具,用于快速,非破坏性地分析和分类食用植物油.
- 该方法能够识别关键脂肪酸概况,从而可以确定原始原料.
- 这种方法符合食品行业对可持续和经济分析解决方案日益增长的需求.
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