Mathematical Model of the Distribution of Stress within a Rice Kernel from Moisture Adsorption

Lan, Yubin; Kunze, O. R.; Laguë, C.; Kocher, M. F.

doi:10.1006/jaer.1998.0368

Cited by 14 publications

(9 citation statements)

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“…A great deal of research beginning the 1930s showed that paddy rice kernels fissure when dried below a critical moisture content and then rehydrate because of exposure to free moisture or high humidity, (Kunze, 1993;Siebenmorgen et al, 1998;Lan et al, 1999). The fissured kernels break during milling, causing low HRY in lots with high amounts of fissured kernels.…”

Section: Abstract California's Medium-grain Rice Industry Experiencementioning

confidence: 99%

“…While maximum HRY was obtained at HMCs above 20%, lots below 18% HMC had nearly the same quality, and lots above 22% moisture had HRY values of less than 50%. The data show that in commercial practice HMC was not a good predictor of HRY, and apparently there must be other variables influencing rice quality.A great deal of research beginning the 1930s showed that paddy rice kernels fissure when dried below a critical moisture content and then rehydrate because of exposure to free moisture or high humidity, (Kunze, 1993;Siebenmorgen et al, 1998;Lan et al, 1999). The fissured kernels break during milling, causing low HRY in lots with high amounts of fissured kernels.…”

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Effect of Weather and Rice Moisture at Harvest on Milling Quality of California Medium-Grain Rice

Thompson¹,

Mutters²

2006

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ABSTRACT. California's medium-grain rice industry experiences a wide range of head rice yield (HRY).he unit value of rice is based primarily on its head rice yield (HRY, the proportion of kernels greater than 75% of intact length; USDA-FGIS, 1994). Improving HRY is an ongoing goal for rice growers. The average moisture content of the paddy rice at harvest (HMC, expressed on a wet weight basis) influences HRY. For medium-grain rice grown in Italy, dry conditions allowed HMC to drop below about 15%, and a subsequent rain caused a significant drop in HRY (Finassi et al., 2002). However, when repeated rain events kept HMC above 20%, HRY was not influenced by HMC. In Louisiana, where rain events are common during rice maturation, long and medium grain rice experienced a significant reduction in HRY when rice dropped below 15.0% to 19.8% HMC depending on variety and year of harvest (Jodari and Lindscombe, 1996). A warmer and drier harvest season caused fissuring to begin at higher HMC than a cooler and more humid season. In two harvest seasons in Arkansas with numerous rain events, HRY was not affected by harvest moistures between 15% and 22% (Siebenmorgen et al., 1992).In California's rice production area, rain is rare and maximum HRY for medium-grain rice is obtained at high HMC. Kester et al. (1963) concluded that the highest HRY is obtained at 25% to 32% HMC. Morse et al. (1967) indicated that HRY peaks between 26% and 30% HMC. Geng et al. (1984) analyzed commercial data, and they concluded that high variability prevented them from finding a narrow range of HMC for high HRY and that HRY was maximum between 25% ±5% HMC. Commercial quality data for California medium-grain rice (D. Jones, Farmers Rice Cooperative, Sacramento, Cal., personal communication, 1999) clearly showed that HMC explains only a small portion of the variability in HRY, as described by the low regression coefficient for a second-order polynomial regression line ( fig. 1). While maximum HRY was obtained at HMCs above 20%, lots below 18% HMC had nearly the same quality, and lots above 22% moisture had HRY values of less than 50%. The data show that in commercial practice HMC was not a good predictor of HRY, and apparently there must be other variables influencing rice quality.A great deal of research beginning the 1930s showed that paddy rice kernels fissure when dried below a critical moisture content and then rehydrate because of exposure to free moisture or high humidity, (Kunze, 1993;Siebenmorgen et al., 1998;Lan et al., 1999). The fissured kernels break during milling, causing low HRY in lots with high amounts of fissured kernels. At harvest, individual kernels vary widely in moisture (Siebenmorgen et al., 1992), and if the pattern of moisture distribution varies because of varying cultural practices or weather conditions, the proportion of kernels below the critical moisture may be a better indicator of HRY than average moisture. Geng et al. (1984) indicated that cycles of drying and moisture absorption may influence quality, but they did no...

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Section: Abstract California's Medium-grain Rice Industry Experiencementioning

confidence: 99%

mentioning

confidence: 99%

Effect of Weather and Rice Moisture at Harvest on Milling Quality of California Medium-Grain Rice

Thompson¹,

Mutters²

2006

Transactions of the ASABE

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“…The main computational method applied with this software was the finite element technique, which divides an elliptical grain kernel into a large number of small triangular elements across a section of the kernel and describes the variation of a field within an element by use of interpolating polynomials (Lague and Jenkins, 1991;Irudayaraj and Haghighi, 1993;Sarker et al, 1996;Lan et al, 1999;Jia et al, 2000aJia et al, , 2000b. In addition, the finite difference method was also used for time domain discretization.…”

Section: Numerical Solution Techniquesmentioning

confidence: 99%

“…the quality evaluation of grains, and has made the tedious and time-consuming heat and mass transfer calculation, optimization, and quality assessment process much easier. Much work has been done to simulate the temperature, moisture content, and stress distributions inside single grain kernels (Haghighi and Segerlind, 1988;Lague and Jenkins, 1991;Irudayaraj and Haghighi, 1993;Sarker et al, 1996;Lan et al, 1999;Jia et al, 2000aJia et al, , 2000b. However, little scientific literature is available discussing the development of userfriendly simulation software for the drying, tempering, and stress analysis of single grain kernels (Jia et al, 1997).…”

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Development of Computer Simulation Software for Single Grain Kernel Drying, Tempering, and Stress Analysis

Jia¹,

Yang²,

Siebenmorgen³

et al. 2002

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The quality traits of a single grain kernel can produce an index of the overall quality of the bulk grain, as individual kernels comprise a grain bulk. Therefore, single-kernel drying behavior is important in understanding the overall quality of grain. A Matlab based software package with C++ compiler was developed in this study for describing single-kernel drying, tempering, and internal stress analysis. Non-linear and transient partial differential heat and mass transfer equations describing the single kernel drying and tempering processes were solved using the finite element method. Temperature-and moisture-dependent viscoelastic properties were applied to the stress analysis of a single rice kernel. A graphical user interface and 2D/3D graphics for temperature, moisture content, and stress changes were developed. This software package is a useful tool for engineers, operators, and educators to predict temperature, moisture content, and internal stress distributions inside a single kernel.

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“…However, simulating the storage of grain is hampered because of insufficient data to predict moisture adsorption rates and effective diffusion coefficients of grains during storage. Only a few studies are available with data on moisture adsorption rates for selected grain materials, especially corn [3], soybeans [4], and rice [5]. There are no sufficient data for modeling moisture adsorption rates of milled rice over a range of storage conditions.…”

Section: Introductionmentioning

confidence: 99%

Moisture Adsorption Rate and Effective Diffusivity in Chinese Milled Rice

Han¹,

Wang²,

ZiDan³

et al. 2017

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Abstract. Four varieties of Chinese milled rice samples with 11.90-15.56% initial moisture content (IMC, wet basis) were used to determine the rate of moisture adsorption using the gravimetric method at 10, 20, 25, 30, and 35°C under 65%, 86%, and 100% relative humidity (RH), respectively. A moisture diffusion equation was modified to fit the relationship between the moisture ratio (MR) of samples and exposure time. In the range of 65% to 100% RH, the lower IMC of milled rice samples corresponded to higher moisture adsorption rate at temperatures of 10 to 35°C. The moisture adsorption rate of samples increased with an increasing temperature. The moisture sorption rate of samples with the same IMC increased with increasing RH at certain temperatures. A single milled rice kernel was geometrically considered a finite homogeneous cylinder shape, and the analytical solution of the partial differential equation of moisture diffusion was given. The effective moisture diffusivity was calculated using a slope method by plotting the experimental data in terms of ln (MR) versus rewetting time. In the range of 10-35°C, the effective moisture adsorption diffusivity of milled rice kernels with normal moisture was 4.321×10 -9 -1.117×10 -7 m 2 h -1 . For the same IMC, the effective moisture diffusivity of milled kernels tended to increase with increases in surrounding temperature at certain relative humidity levels, but decreased with an increase in RH at certain temperatures. It was concluded that the milled rice samples from different types had similar effective moisture diffusivity when similar IMC was given.

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Mathematical Model of the Distribution of Stress within a Rice Kernel from Moisture Adsorption

Cited by 14 publications

References 1 publication

Effect of Weather and Rice Moisture at Harvest on Milling Quality of California Medium-Grain Rice

Effect of Weather and Rice Moisture at Harvest on Milling Quality of California Medium-Grain Rice

Development of Computer Simulation Software for Single Grain Kernel Drying, Tempering, and Stress Analysis

Moisture Adsorption Rate and Effective Diffusivity in Chinese Milled Rice

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