使用完整蛋白质流动注射质谱指纹图谱结合化学计量学快速检测牛奶掺假。
Rapid detection of milk adulteration using intact protein flow injection mass spectrometric fingerprints combined with chemometrics.
作者信息
Du Lijuan, Lu Weiying, Cai Zhenzhen Julia, Bao Lei, Hartmann Christoph, Gao Boyan, Yu Liangli Lucy
机构信息
Institute of Food and Nutraceutical Science, Department of Food Science and Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.
Institute of Food and Nutraceutical Science, Department of Food Science and Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Nestlé Food Safety Institute, Nestlé R&D (China) Ltd., 100095 Beijing, China.
出版信息
Food Chem. 2018 Feb 1;240:573-578. doi: 10.1016/j.foodchem.2017.07.107. Epub 2017 Jul 25.
Flow injection mass spectrometry (FIMS) combined with chemometrics was evaluated for rapidly detecting economically motivated adulteration (EMA) of milk. Twenty-two pure milk and thirty-five counterparts adulterated with soybean, pea, and whey protein isolates at 0.5, 1, 3, 5, and 10% (w/w) levels were analyzed. The principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and support vector machine (SVM) classification models indicated that the adulterated milks could successfully be classified from the pure milks. FIMS combined with chemometrics might be an effective method to detect possible EMA in milk.
对流动注射质谱法（FIMS）结合化学计量学用于快速检测牛奶中出于经济动机的掺假（EMA）情况进行了评估。分析了22份纯牛奶以及35份分别掺入0.5%、1%、3%、5%和10%（w/w）水平的大豆、豌豆和乳清分离蛋白的掺假牛奶。主成分分析（PCA）、偏最小二乘判别分析（PLS - DA）和支持向量机（SVM）分类模型表明，掺假牛奶能够成功地与纯牛奶区分开来。流动注射质谱法结合化学计量学可能是检测牛奶中潜在EMA的有效方法。
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