Oui-Woung Kim

Milling Characteristics of Milled Rice According to Milling Ratio of Friction and Abrasive Milling

This study was performed to investigate the optimum abrasive and friction milling ratio. This was accomplished by determining changes in the quality, such as whiteness, moisture content, broken kernel, unstripped embryo rate, and surface characteristics or milling difference, during an abrasive and friction based milling process. When only abrasive was milled, the increase of whiteness was fast in the first milling, whereas the increasing rate of whiteness was small in the latter milling. The decreasing rate of moisture content and broken kernel increased as the friction milling ratio was increased. Combining with the friction milling was considered a suitable method because the unstripped embryo rate was high only when abrasive milling was used. In the case of a high abrasive milling ratio, a significant milling difference was observed in the initial milling. This indicated that the milling difference was not completely eliminated despite using friction milling in the latter milling. Consequently, it was necessary to minimize the milling difference in the initial milling. When milling quality was synthetically considered, the abrasive milling ratio was varied from 20~50%. When the abrasive milling ratio was greater than 40%, the external quality of the rice milled deteriorated since holes and defects generated on the surface in the initial milling were not removed. Due to this deterioration in surface characteristics, an abrasive milling ratio of 30% was identified as a suitable level.

Thin Layer Drying Model of Sorghum

Hong-Sik Kim, Oui-Woung Kim, Hoon Kim, Hyo-Jai Lee, Jae-Woong Han* Research Group of Smart Food distribution system, Korea Food Research Institute, Sungnam 13539 Korea Division of Bio-Industry Engineering, Koungju National University, Yesan, 32439 Korea Received: August 31st, 2016; Revised: September 26th, 2016; Accepted: November 5th, 2016 Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature (40°C, 50°C, and 60°C) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was 40°C at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was 60°C at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.

Effects of Abnormal Kernels in Brown Rice on Milling Characteristics

This study was conducted to find out effects of abnormal kernels of 0 to 30% in brown rice on quality characteristics during milling using friction type test mill. The average hardness values of abnormal and normal brown rice kernels were 6.52 kg, 8.48 kg, respectively. According to the increase of abnormal kernels in brown rice, grain temperature, required electrical energy, the broken kernels ratio, and the weight of solid matter on the surface of milled rice were increased due to crush of the abnormal kernels during milling, which proves that abnormal kernels in brown rice should be removed before milling to improve milling characteristics.

Simulation of Wheat Circulating Cross-flow Dryer

Purpose: In Korea, wheat is dried using circulating cross-flow grain dryers. However, there is no research on wheat drying which can be utilized for the dryers. Therefore, this study developed and evaluated a simulation of the circulating cross-flow dryer, and examined the effects of various factors on drying performance. Methods: The simulation program was developed using drying models and was evaluated against wheat-drying experiments with a dryer having a 30-ton capacity. The influence of drying temperature, air volume, and grain falling rate on drying performance were examined through the simulation. Results: The experimental results validated the simulation program by showing the same root mean square error (RMSE) for moisture content (0.286%) and drying rate (0.056%/h) in both the experimental data and the simulation values. The appropriate wheat-drying parameter values, considering drying conditions, were determined to be 50°C for drying temperature, 500 m 3 /min for air volume, and a grain falling rate of 36.0 m 3 /h. Conclusions: The developed simulation program for circulating cross-flow dryers analyzed the influences of performance factors such as drying temperature, air volume, and falling rate on drying performance.

Combine Harvest Scheduling Program for Rough Rice using Max-coverage Algorithm

Purpose: This study was conducted to develop an optimal combine scheduling program using Max-Coverage algorithm which derives the maximum efficiency for a specific location in harvest seasons. Methods: The combine scheduling program was operated with information about combine specification and farmland. Four operating types (Max-Coverage algorithm type, Boustrophedon path type, max quality value type, and max area type) were selected to compare quality and working capacity. Result: The working time of Max-Coverage algorithm type was shorter than others, and the total quality value of Max-Coverage algorithm and max quality value type were higher than others. Conclusion: The developed combine scheduling program using Max-Coverage algorithm will provide optimal operation and maximum quality in a limited area and time.