Impact of rewetting and drying of rough rice on predicted moisture content profiles during in-bin drying and storage

Accurate prediction of moisture content (MC) is vital for effective control of on-farm, in-bin drying and storage of rough rice, especially for systems using recently introduced technology to automate fan run time. The study used simulations, laboratory, and field experiments to investigate the extent to which rewetting and drying, during in-bin drying and storage, affect accuracy of predicted MC-a critical parameter for automated fan control. Vapor sorption analysis (VSA) was used to generate MC prediction models for rough rice. Simulations of in-bin drying and storage, using in-field weather data, were performed while segregating effects resulting from rewetting and drying of the rough rice and the type of fan control strategy used. Predicted MC profiles of rough rice and drying durations were compared with those resulting from using standard constants in the literature for modeling. The root mean square error associated with predicting the MC by model constants developed using the VSA was 0.54% MC and 1.32% MC dry basis (d.b.), for desorption and adsorption, respectively. Deviation in MC logged by in-bin built, field sensors and that simulated by taking into account the influence of rewetting and drying were generally within 1.5% point difference. Therefore, rewetting and drying did not affect drying duration. However, drying duration was significantly influenced by fan control strategy (p < 0.05). It was concluded that under the same fan control strategy, the effect of rewetting and drying on predicted rough rice MC was negligible.