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利用可见拉曼光谱定量分析动物脂肪混合物中的猪油。

Quantitative analysis of lard in animal fat mixture using visible Raman spectroscopy.

机构信息

Department of Chemistry, School of Physics and Chemistry, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea.

Advanced Photonics Research Institute, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea.

出版信息

Food Chem. 2018 Jul 15;254:109-114. doi: 10.1016/j.foodchem.2018.01.185. Epub 2018 Feb 1.

Abstract

Food adulteration is a serious issue that requires verification and strict management due to healthcare, morality, and social value problems. In the context of fat, food manufacturers blend lard with vegetable oils or animal fats for convenience and gaining economic benefits. Thus, we herein report the classification of 4 animal fats, e.g., beef tallow, pork lard, chicken fat, duck oil, using Raman spectroscopy combined with simple calculation of intensity ratios of Raman signal at vibrational modes corresponding to unsaturated fatty acids and total fatty acids. Various calculated values of the species were compared to find a feature that is able to classify each fats using Raman peak ratio. As a result, we suggested "Oil gauge (OG)" as a standard feature for classification of the fats in Raman analysis field. Furthermore, a quantification of the lard in other fat was accomplished with good linear correlation using the OG values.

摘要

食品掺假是一个严重的问题,由于医疗保健、道德和社会价值问题,需要进行验证和严格管理。在脂肪方面,食品制造商为了方便和获取经济利益,将猪油与植物油或动物脂肪混合。因此,我们在此报告了 4 种动物脂肪(如牛脂、猪脂、鸡脂和鸭油)的分类,使用拉曼光谱结合对应于不饱和脂肪酸和总脂肪酸的振动模式的拉曼信号强度比的简单计算。比较了各种物种的计算值,以找到一个能够使用拉曼峰比对每种脂肪进行分类的特征。结果表明,我们建议将“油表(OG)”作为拉曼分析领域中脂肪分类的标准特征。此外,还使用 OG 值完成了其他脂肪中猪油的定量,具有良好的线性相关性。

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