Abstract Beta-Lactoglobulin (β-Lg) is the major fraction of whey protein that comprises more than 65%. Therefore, denaturation of β-Lg during drying can affect the protein functionality where the whey protein is used as an ingredient in food products. This study was carried out to understand the drying and denaturation kinetics of β-Lg during the drying process. A convective drying environment was used to predict the moisture content and temperature kinetics of the drying droplets of β-Lg using Reaction Engineering Approach (REA) models. The predicted values were then coupled with the first order reaction equation to determine the denaturation kinetics. Single droplets of β-Lg (10% w/v; 1.5 ± 0.1 mm initial diameter) were dried at two different temperatures (65 °C and 80 °C) at a constant air velocity (0.5 m/s) for 10 min. The real time denaturation of β-Lg protein was quantified at different drying stages using a reversed phase HPLC. These experimental data from single droplet drier, and HPLC were used to validate the model predictions. The REA model predictions fitted well with the experimental data for moisture-time (±5.70% error) and temperature-time (±3.50% error) profiles. Similarly, the first order kinetics model was also able to predict the denaturation kinetics of β-Lg protein with an average error of 6.00%. The conformation study by FTIR observed that the drying stress increased the secondary structural properties random coil and β-sheet which was compensated by uncoiling of α-helix and transformation of β-turn into β-sheet. The morphology study found that initially β-Lg droplet showed flexible nature but formed firm skin with increasing drying time.

中文翻译：

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β-乳球蛋白在对流干燥过程中的干燥和变性动力学

摘要 β-乳球蛋白 (β-Lg) 是乳清蛋白的主要成分，占 65% 以上。因此，干燥过程中 β-Lg 的变性会影响使用乳清蛋白作为食品成分的蛋白质功能。本研究旨在了解 β-Lg 在干燥过程中的干燥和变性动力学。使用反应工程方法 (REA) 模型，使用对流干燥环境来预测 β-Lg 干燥液滴的水分含量和温度动力学。然后将预测值与一级反应方程结合以确定变性动力学。单滴 β-Lg（10% w/v；1.5 ± 0.1 mm 初始直径）在两种不同温度（65 °C 和 80 °C）下以恒定空气速度 (0.5 m/s) 干燥 10 分钟。β-Lg 蛋白的实时变性在不同干燥阶段使用反相 HPLC 进行定量。这些来自单液滴干燥器和 HPLC 的实验数据用于验证模型预测。REA 模型预测与湿度-时间（±5.70% 误差）和温度-时间（±3.50% 误差）曲线的实验数据非常吻合。同样，一级动力学模型也能够以6.00%的平均误差预测β-Lg蛋白的变性动力学。FTIR的构象研究观察到干燥应力增加了无规卷曲和β-折叠的二级结构特性，这通过α-螺旋的解卷和β-转角向β-折叠的转化得到补偿。形态学研究发现，最初 β-Lg 液滴表现出柔韧的性质，但随着干燥时间的增加，形成了紧实的皮肤。