Department of Food Engineering, Faculty of Engineering, Hacettepe University, Beytepe, 06800, Ankara, Turkey.
J Food Drug Anal. 2019 Jan;27(1):101-110. doi: 10.1016/j.jfda.2018.06.008. Epub 2018 Jul 4.
The adulteration of milk fat in dairy products with cheaper non-milk based fats or oils is frequently encountered in the dairy industry. In this study, Raman spectroscopy with chemometric was used for the discrimination of foreign fats and oils in milk cream and yogurt. Firstly, binary mixtures of cream and oils (corn and sunflower oil), and vegetable fat blends which are potentially or currently used by the dairy industry were prepared. All fat or oil samples and their binary mixtures were examined by using Raman spectroscopy. Then, fat content of skim milk was adjusted to 3% (w/w) by the milk fat, external oils or fats, and binary mixtures, and was used in yogurt production. The lipid fraction of yogurt was extracted and characterized by Raman spectroscopy. The spectral data were then pre-processed and principal component analysis (PCA) was performed. Raman spectral data showed successful discrimination for about the source of the fats or oils. Temperature effect was also studied at six different temperatures (25, 30, 40, 50, 60 and 70 °C) in order to obtain the best spectral information. Raman spectra collected at higher temperatures were more intense. Obtained results showed that the performance of Raman spectroscopy with PCA was very promising and can be expected to provide a simple and quick way for the discrimination of foreign fats and oils in both milk cream and yogurt. Fermentation and yogurt processing affected clustering of fat samples by PCA, probably depending on some lipolysis or production of new products that can affect the Raman scattering. However, those changes did not affect differentiation of samples by Raman spectroscopy.
乳制品中牛奶脂肪被更廉价的非乳基脂肪或油类掺假的情况在乳制品行业中经常出现。本研究采用拉曼光谱结合化学计量学方法对奶油和酸奶中的外来脂肪和油进行鉴别。首先，制备了奶油和油（玉米油和葵花籽油）的二元混合物，以及乳制品行业潜在或当前使用的混合植物油。使用拉曼光谱检查所有脂肪或油样品及其二元混合物。然后，通过添加牛奶脂肪、外部油或脂肪以及二元混合物，将脱脂奶的脂肪含量调整至 3%（w/w），并用于生产酸奶。通过拉曼光谱对酸奶的脂质部分进行提取和特征描述。然后对光谱数据进行预处理，并进行主成分分析（PCA）。拉曼光谱数据成功地对脂肪或油的来源进行了区分。为了获得最佳的光谱信息，还研究了在六个不同温度（25、30、40、50、60 和 70°C）下的温度效应。在较高温度下收集的拉曼光谱更强烈。结果表明，拉曼光谱结合 PCA 的性能非常有前景，可以预期为鉴别奶油和酸奶中的外来脂肪和油提供一种简单快捷的方法。发酵和酸奶加工通过 PCA 影响脂肪样品的聚类，可能取决于一些脂肪水解或产生新的产品，这可能会影响拉曼散射。然而，这些变化并没有影响拉曼光谱对样品的区分。
