Abstract
The steaming process is crucial for the production of stuffed buns. This study aimed to monitor quality changes in stuffed buns during steaming and to simulate internal temperature evolution using numerical modeling, to support intelligent process control. Multiple quality attributes were evaluated during steaming, and internal temperature distributions were monitored at the bun center and at radial distances of 1, 2, and 3 cm from the center. A numerical temperature model was established and validated by comparison with experimental measurements. The results showed that most quality indicators exhibited the most pronounced changes during the initial 0-9 min of the steaming process. Among the evaluated parameters, internal temperature was identified as the most suitable indicator for monitoring the steaming state of stuffed buns. The consistency between simulated and experimental temperature profiles further confirmed the feasibility of the proposed temperature-based monitoring approach. This study provides a theoretical and technical basis for the intelligent monitoring and control of stuffed bun steaming.