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The Selection of Sorption Isotherm for Rough Rice

M. Moniruzzaman
Dept. of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.

M. A. Basunia
Dept. of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.

M. Rostom All
Dept. of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.

Abstract/ Executive Summary:

Eighteen sources of Equilibrium Moisture Content (EMC) and Equilibrium Relative Humidity (ERH) data for rough rice were obtained which contain 588 data points, comprising 349 desorption and 239 adsorption. Fifteen commonly cited EMC/ERH equations were compared for their ability to fit the available observed EMC/ERH data for rough rice, Eight two-parameter. four three-parameter and three four-parameter equations were compared for their ability to fit the experimental EMC/ERH data. The Residual Sum Square (RSS), Standard Error of Estimate (SEE) and coefficient of Regression (R²) was adapted as the criteria to evaluate the fitting performance of the models. The three-parameter Modified Chungh-Pfost (MCP) equation was identified as the most appropriate equation for representing the EMC/ERH isotherms of rough rice, The MCP was then used to fit the data sets in turns. The best fitted coefficients of MCP for both ERH as a function of EMC and EMC as a function of ERH and temperature are given. These fitted equations provide a useful basis for simulation of drying and storage systems of rough rice.

Keywords: Sorption, Rice, Equilibrium Moisture Content ,Equilibrium Relative Humidity

Location: Dept. of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh

Start Date:

End Date:

Program Area: Variety and Species

Commodity: Rice

Objectives:

To verify the ability of the commonly used two-, three- and four- parameter EMC/ERH models to fit the available EMC/ERH observed data of rough rice and
To identify the best fitted equation for rough rice among the selected two-, three- and four- parameter equations.

Methodology:

The experiment was conducted at Dept. of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh, Bangladesh. Fifteen isotherm equation were selected for fitting the observed adsorption and desorption isotherm data of rough rice. The experimental EMC/ERH data were obtained from 18 sources, which contains 588 EMC data (Moniruzzaman 2002). In this study, therefore, commonly used two, three and four parameter equation for grains were used to compare their fitting in both froms, to the experimental data. To select the most appropriate equation, a statistical package (SPSS-1997) was used to fit the EMC/ERH data of rough rice. The SPSS package is an easy way for finding an unconstrained minimum of the sum of square of m nonlinear functions with n variables and to estimate the parameters for nonlinear regression models.The following two error parameters were used to compare the fitting ability of EMC/ERH models for rough rice. The same parameters were also used in the study as criteria for selection of EMC/ERH isotherm equation for grain.The residual sum of squares (RSS) is an important error parameter during the nonlinear curve fitting process. The SPSS package was designed to find minimum of the RSS during fitting. The RSS is defined as follows

RSS = ∑(M-Ms)²

Where, Ms in the simulated value of M.

The standard error of estimate (SEE) indicates the fitting ability of a model to a data set. The smaller SEE value indicates the better fitting ability of an equation. For the same data set, the equation giving the smallest SEE value represents the best fitting ability (Basunia & Abe 1999, 2001). The standard error of estimate (SEE) shows the deviation of the dependent variable M and is given by

SEE =√∑(M-Ms)²

Where, df is the degree of freedom.

Source of Information: Bangladesh J. Agri. Engg. 15 (1 & 2) 19-30 : 2004

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

Fifteen commonly cited EMC/ERH equations were compared for their ability to fit the observed EMCIERFI data of the rough rice. Among the selected eight two-parameter equations the Henderson model was the best. Among the three-parameter equations the Modified Chung-Pfost model was the best. Among the four-parameter equations the Chen-Clayton model was the best. Among the selected two-, three- and four-parameter models the three-parameter Modified Chung-Pfost model was found to be the most appropriate equation for representing the rough rice adsorption, desorption and corthined EMC/ERH isotherms. The Modified Chung-Pfost mode] is, therefore recommended for prediction of the adsorption and desorption isotherms for rough rice. The equations fitted here are based on larger data sets provided a sound basis for future work on drying and storage.

Knowledge Management: Journal