Institute of Chemical Technologies and Analytics, Vienna University of Technology, Getreidemarkt 9/164-UPA, 1060 Vienna, Austria.
Analyst. 2019 Sep 9;144(18):5571-5579. doi: 10.1039/c9an00746f.
Analysis of bovine milk proteins is crucial in many food and non-food industrial applications, nevertheless labour-intensive wet-chemical, low-throughput methods are still routinely used. In this work, external cavity-quantum cascade laser (EC-QCL) mid-infrared spectroscopy is employed as a rapid method for protein analysis of commercial bovine milk. Combined analysis of the amide I and II bands enabled quantitation of individual proteins (casein, β-lactoglobulin, α-lactalbumin) and total protein content. IR spectra of spiked and diluted milk samples were employed for calibration of the target analytes in the presence of a complex matrix by partial least squares (PLS) regression modelling. A sample set of different milk types (pasteurized; differently processed extended shelf life, ESL; ultra-high temperature, UHT) was analysed, and results agreed well with reference methods. Quantitation of temperature sensitive proteins enables detailed distinction between milk types experiencing different heat loads during processing, and discrimination between diverse bovine milk types is successfully demonstrated.
分析牛乳蛋白在许多食品和非食品工业应用中至关重要，但目前仍常规使用劳动密集型的湿法化学、低通量方法。在这项工作中，外腔量子级联激光（EC-QCL）中红外光谱被用作商业牛乳中蛋白质快速分析的方法。酰胺 I 和 II 带的组合分析能够定量个别蛋白质（酪蛋白、β-乳球蛋白、α-乳白蛋白）和总蛋白质含量。通过偏最小二乘（PLS）回归建模，在复杂基质存在的情况下，对加标和稀释牛乳样品的 IR 光谱进行了目标分析物的校准。分析了不同牛乳类型（巴氏杀菌；不同处理的延长货架期，ESL；超高温，UHT）的样品集，结果与参考方法吻合良好。对温度敏感蛋白质的定量能够对加工过程中经历不同热负荷的牛乳类型进行详细区分，并且成功地证明了不同的牛乳类型之间的区分。
