Analysis Of Corn Drying Function Model Based On SPSS

Drying is an important part of corn processing and storage after harvest, having a great influence of corn quality. Reasonable drying technology and parameters are important methods of improving the quality of dry corn. This article adopts the method of combining theoretical analysis with experimental research, to validate and research the important parameters in the process of corn drying. The significance is to improve the drying efficiency, reduce energy consumption and ensure the quality. This article adopts the method of orthogonal experiment, carrying out three factors, four levels of the corn drying experiments, to analyze the effects of experimental factors on the corn drying characteristics. Under condition of different humidity(55%, 60%, 65%, 70%), Choosing corn drying experiment data as the measured sample, based on SPSS software, using regression analysis method, make use of the data to solve the traditional drying models, obtaining the dry coefficients. Through the evaluation indexes of determination coefficient R2 and F to evaluate all kinds of drying models, finally use the experimental data for validation. The results show that the Page model is the optimal model. This model can accurately predict the corn moisture content and drying rate of each drying stage, applied to determine reasonable drying parameters, to achieve the goal of regulating dry environment and improving efficiency.