Elshereef Rand, Budman Hector, Moresoli Christine, Legge Raymond L
Department of Chemical Engineering, University of Waterloo, Waterloo, Ont., Canada.
Biotechnol Bioeng. 2006 Dec 5;95(5):863-74. doi: 10.1002/bit.21039.
Denaturation and aggregation of whey proteins are of interest to the food and pharmaceutical industry due to the importance of final structure in functionality, impact on food texture, and the chemical stability of the final product. In this study, we demonstrate the potential of fluorescence spectrometry combined with multivariate chemometric methods for quantifying solubility and aggregation behavior of beta-lactoglobulin (beta-LG); a major whey protein and a frequent food ingredient. Heat-induced aggregation of beta-LG was studied under different conditions including pH, temperature and heating durations. Results showed very good agreement between the fluorescence-based predictions and measurements obtained by HPLC and gravimetric analysis regardless of the conditions. Standard normal variate (SNV), a signal preprocessing and filtering tool, was found to enhance the predictive accuracy and robustness of the fluorescence-based model.
由于最终结构在功能方面的重要性、对食品质地的影响以及最终产品的化学稳定性，乳清蛋白的变性和聚集受到食品和制药行业的关注。在本研究中，我们展示了荧光光谱法结合多元化学计量方法用于定量β-乳球蛋白（β-LG）的溶解度和聚集行为的潜力；β-LG是一种主要的乳清蛋白且是常见的食品成分。在不同条件下研究了β-LG的热诱导聚集，包括pH值、温度和加热持续时间。结果表明，无论在何种条件下，基于荧光的预测结果与通过高效液相色谱法（HPLC）和重量分析获得的测量结果都非常吻合。发现标准正态变量变换（SNV）这种信号预处理和滤波工具可提高基于荧光的模型的预测准确性和稳健性。
