Five commonly cited thin-layer rewetting models, that is, Diffusion, Page, Exponential, Approximate form of diffusion and Polynomial were compared for their ability to fit the experimental re-wetting data of medium grain of rough rice, based on the standard error of estimate (SEE) of the measured and simulated moisture contents. The comparison shows that the Diffusion and the Page models have almost the same ability to fit the re-wetting experimental data of rough rice. The Exponential, the Approximate form of diffusion and the Polynomial models have less fitting ability than the Diffusion and the Page models for the entire period (> 4 days) of re-wetting of 25 tests at different combinations of temperatures (17.8 to 45°C) and relative humidites (56.0 to 89.3%). The Diffusion and the Page models were found to be most suitable equations, the average SEE value was less than 0.0015 (dry-basis, decimal), respectively, to describe the thin-layer re-wetting characteristics of rough rice over a typical five day re-wetting. These two models can be used for the simulation of deep-bed re-wetting of rough rice occurring during ventilated storage.
Key words: Thin-layer, rough rice, re-wetting parameters, temperature, relative humidity.
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