Efficient production of milk powder with good quality that can pass strict functional tests is of primary concern for most milk processing plants, making the online prediction of production quality a popular research topic in recent years. Rehydration is an important quality indicator for instant whole milk powder and is mainly affected by process variables and morphology of the powder. This work investigated the feasibility of using both morphology metrics and process variables to develop on-line, or at-line, sensors for the prediction of rehydration of instant whole milk powder. Two key properties, namely dispersibility and slowly dissolving particles are the focus of this study. Light microscopy with image processing were used to obtain quantitative information on different shape factors of the milk powders, before using resampling to solve the class imbalances in the original dataset. Various partial least squares models constructed from (i) process variables only, (ii) shape factor variables only, and (iii) process variables combined with shape factor variables were used to compare which variables are important in developing soft sensors for predicting the dispersibility and slowly dissolving particles of instant whole milk powder. It was found that the dispersibility of instant whole milk powder mainly depends primarily on the shape factor variables while the process variables and shape factor variables are both important to predict slowly dissolving particles of instant whole milk powder. The good performance of the models (the Q² is 0.77 and 0.94, respectively, while the R² is 0.93 and 0.97, respectively) developed by process variables and shape factor variables also indicated that this approach could be used in real-time to measure the rehydration properties of milk powder and could be used for developing online model-based process monitoring.

如何通过严格的功能测试来生产高质量的优质奶粉是大多数牛奶加工厂的首要考虑因素，因此，在线预测生产质量成为近年来流行的研究主题。补液是速溶全脂奶粉的重要质量指标，主要受制于工艺变量和奶粉形态的影响。这项工作研究了使用形态学指标和过程变量来开发在线或在线传感器来预测速溶全脂奶粉补水的可行性。这项研究的重点是两个关键特性，即分散性和缓慢溶解的颗粒。使用光学显微镜和图像处理技术获得了有关奶粉不同形状因子的定量信息，在使用重采样解决原始数据集中的类不平衡之前。各种偏最小二乘模型仅由（i）过程变量，（ii）仅形状因子变量和（iii）过程变量与形状因子变量组合而成，用于比较哪些变量在开发软传感器以预测分散性和将速溶全脂奶粉的颗粒缓慢溶解。发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（各种偏最小二乘模型仅由（i）过程变量，（ii）仅形状因子变量和（iii）过程变量与形状因子变量组合而成，用于比较哪些变量在开发软传感器以预测分散性和将速溶全脂奶粉的颗粒缓慢溶解。发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（各种偏最小二乘模型仅由（i）过程变量，（ii）仅形状因子变量和（iii）过程变量与形状因子变量组合而成，用于比较哪些变量在开发软传感器以预测分散性和将速溶全脂奶粉的颗粒缓慢溶解。发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（（iii）使用过程变量与形状因子变量相结合，比较哪些变量对开发软传感器以预测速溶全脂奶粉的可分散性和缓慢溶解颗粒很重要。发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（（iii）使用过程变量与形状因子变量相结合，比较哪些变量对开发软传感器以预测速溶全脂奶粉的可分散性和缓慢溶解颗粒很重要。发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（发现速溶全脂奶粉的分散性主要取决于形状因子变量，而工艺变量和形状因子变量对于预测速溶全脂奶粉的颗粒的溶解都很重要。模型的良好性能（Q ^2分别为0.77和0.94，而R ²分别为0.93和0.97（由过程变量和形状因子变量开发）也表明，该方法可以实时用于测量奶粉的补水特性，并且可以用于开发基于模型的在线过程监控。