Prediction Impact of Vacuum Drying Parameters on Rice Taste Value with Neural Network Model

Process control over rice vacuum drying directly affects the taste quality of dried rice. Drying temperature, initial rice moisture content and vacuum degree are the main parameters that affect rice-drying process. This paper makes research on the change law of taste quality of brown rice versus drying parameters during vacuum drying process through establishment of neural network model between brown rice taste value and drying parameters, which will provide reference for objective evaluation on rice taste, dried rice quality and the design of vacuum dryer. The results show that, BP neural network model predicts the average relative error of 2.88%, correlation coefficient of 0.96, BP neural network can serve as a new model for description of rice taste value of vacuum drying.