Journal of
Stored Products and Postharvest Research

  • Abbreviation: J. Stored Prod. Postharvest Res.
  • Language: English
  • ISSN: 2141-6567
  • DOI: 10.5897/JSPPR
  • Start Year: 2010
  • Published Articles: 165

Full Length Research Paper

Best fitted thin-layer re-wetting model for medium-grain rough rice

M. A. Basunia1* and M. A. Rabbani2
1Department of Soils, Water and Agricultural Engineering, Sultan Qaboos University, P. O. Box 34, Al-Khod 123, Muscat, Sultanate of Oman. 2Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh.
Email: [email protected]

  •  Accepted: 11 August 2011
  •  Published: 08 September 2011


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.