谷朊粉颗粒热风干燥动力学模型及水分迁移规律

为了探究谷朊粉颗粒热风干燥过程中的干燥特性及水分迁移规律，开展了谷朊粉颗粒2因素3水平全因素热风干燥试验，考察不同干燥温度（50、60、70 °C）和颗粒厚度（4.24、9.15、15.52 mm）下的干燥特性，运用低场核磁共振技术分析了干燥过程中的水分迁移规律，并建立干燥动力学模型和水分预测模型。结果表明:谷朊粉颗粒干燥速率和水分比随温度升高而显著降低（P＜0.05）；有效水分扩散系数随温度升高和颗粒厚度增加而增大。决定系数（R2）、离差平方和（\begin{document}$ {\chi }^{2} $\end{document}）、均方根误差（RMSE）计算结果表明，Modified Page薄层干燥模型对谷朊粉颗粒的干燥试验数据具有较高的拟合精度，而且建立了模型参数（k、n）与干燥温度（T）、颗粒厚度（H）的回归模型（R2＞0.926）。低场核磁共振横向弛豫时间（T₂）反演谱显示，随干燥时间的增加，各水分峰面积逐渐减小，而且峰位置逐渐向结合水靠近，并建立了含水率（M）与干燥时间（t）、颗粒厚度（H）、干燥温度（T）、弛豫反演图谱总峰面积（A）之间的回归关系，结果表明预测效果较好（R2=0.933）。研究结果可为谷朊粉颗粒干燥工艺提供参考。 

Dynamic model and law of moisture migration of gluten pellets during hot air drying

A two-factor three-level full-factor hot air drying experiment was carried out at different drying temperatures（50, 60, 70 °C）and pellet thicknesses（4.24, 9.15, 15.52 mm）, in order to explore drying characteristics and moisture migration law of gluten pellets． Low-field nuclear magnetic resonance technology was used to analyze moisture migration law in drying process, and a drying kinetic model and moisture prediction model was established． Rresults showed that drying rate and moisture ratio of gluten pellets decreased significantly with increase of temperature（P<0.05）． Effective water diffusion coefficient increaseed with temperature and pellet thickness raising． Calculation results of determination coefficient（R2）, sum of squares of deviation（\begin{document}$ {\chi }^{2} $\end{document}）and root mean square error（RMSE）show that Modified Page thin layer drying model had high fitting accuracy to drying test data of gluten pellets． And regression model of model parameters（k,n）, drying temperature（T）and pellet thickness（H）was established（R2＞0.926）． Low-field nuclear magnetic resonance transverse relaxation time（T₂）inversion spectrum showed that peak area of each moisture gradually decreased, and peak position gradually approached bound water with increase of drying time． Relationship between moisture content（M）and drying time（t）, pellet thickness（H）, drying temperature（T）, total peak area（A）of relaxation inversion spectrum was established． Results showed that prediction accuracy was high（R2=0.933）． Research results could provide reference for drying process of gluten pellets．