In a previous paper, we reported on the performance of a device developed for rice seed disinfection. To treat the rice seed such that its temperature after heating (Tfin) is 75±1°C,the device elicits a control effect equivalent to or more effective than the conventional hot water treatment against rice seed-borne diseases, and without the negative effect of excess heat on seed germination. In this study, we aimed to develop a process control method for Tfin using Predictive Functional Control. In particular, we aimed to calibrate and validate a prediction model for Tfin using the process conditions of the device. We created a multiple linear regression model to predict Tfin, which uses gas humidity, heating time, and other process conditions as predictor variables. The model can predict Tfin within the standard error of 0.5°C in the range of 66.0 to 82.7°C. This result indicates that it is possible to apply the model for device operation and control.
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