State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province 214122, China; Department of Animal Science, Faculty of Agriculture, National University of Lesotho, Roma 180, Lesotho, Southern Africa.
State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu Province 214122, China.
J Dairy Sci. 2013 Apr;96(4):2130-2136. doi: 10.3168/jds.2012-6417. Epub 2013 Feb 15.
This study assessed the potential application of fluorescence spectroscopy in detecting adulteration of milk fat with vegetable oil and characterizing the samples according to the source of the fat. Pure butterfat was adulterated with different vegetable oils at various concentrations (0, 5, 10, 15, 20, 30, and 40%). Nonfat and reduced-fat milk were also adulterated with vegetable oils to simulate full-fat milk (3.2%). The 2- and 3-dimensional front-face fluorescence spectroscopy and gas chromatography were used to obtain the fluorescence spectra and fatty acid profile, respectively. Principal component analysis and 3-way partial least squares regression analysis were applied to analyze the data. The pure and adulterated samples were discriminated based on the total concentration of saturated fatty acids and unsaturated fatty acids, and also on the 3 major fluorophores: tryptophan, tocopherols, and riboflavin. Fluorescence spectroscopy was able to detect up to 5% of adulteration of vegetable oil into the butterfat. The saturated fatty acids showed higher predictability than the unsaturated fatty acids (R(2) = 0.73-0.92 vs. 0.20-0.65, respectively). The study demonstrated the high potential of fluorescence spectroscopy to rapidly detect adulteration of milk fat with vegetable oil, and discriminate commercial butter and milk according to the source of the fat.
本研究评估了荧光光谱法在检测乳脂中植物油掺假以及根据脂肪来源对样品进行特征分析方面的潜在应用。将纯乳脂与不同浓度(0、5、10、15、20、30 和 40%)的植物油混合。非脂乳和低脂乳也被植物油掺假以模拟全脂乳(3.2%)。采用二维和三维前向荧光光谱法和气相色谱法分别获得荧光光谱和脂肪酸图谱。主成分分析和三向偏最小二乘回归分析用于分析数据。基于饱和脂肪酸和不饱和脂肪酸的总浓度,以及色氨酸、生育酚和核黄素这 3 种主要荧光团,对纯品和掺杂物进行了区分。荧光光谱法能够检测到高达 5%的植物油对乳脂的掺假。饱和脂肪酸的预测能力高于不饱和脂肪酸(分别为 0.73-0.92 和 0.20-0.65)。该研究表明,荧光光谱法具有快速检测乳脂中植物油掺假的高潜力,并能根据脂肪来源区分商业黄油和牛奶。