• Food Science and Preservation
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• v.17 no.1
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• pp.16-22
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• 2010

To maintain the storage quality of agricultural products, temperature uniformity during cold storage, which is affected by fan flow rate and product arrangement, is important. We simulated and validated a CFD (Computational Fluid Dynamics) model that can predict both airflow and temperature distribution in a cold storage environment. Computations were based on a commercial code (FLUENT 6.2) and two turbulence models. The standard k-$\varepsilon$ model and the Reynolds stress model (RSM) were chosen to improve the accuracy of CFD prediction. To obtain comparative data, the temperature distribution and velocity vector profiles were measured in a full-scale cold storage facility and in a 1/5 scale model. The agricultural products domain in cold storage was modeled as porous for economical computation. The RSM prediction showed good agreement with experimental data. In addition, temperature distribution was simulated in the cold storage rooms to estimate the uniformity of temperature distribution using the validated model.

• Journal of Food Hygiene and Safety
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• v.24 no.2
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• pp.169-173
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• 2009

A survey of total aflatoxin levels was conducted on 145 samples(carthamiflos, thujae semen, giycyrrhizae radix et rhizoma) collected in Yakyeang markets in Seoul. Aflatoxin levels were quantified by the immunoaffinity column clean-up method followed by performance liguid chromatography(HPLC)-fluorescence detector(FLD). Aflatoxins were found in 10(6.9%)samples including 5 Arecae semen, 4 Thujae semen, 1 Zizyphi semen with a range of $0.45{\sim}79.15\;{\mu}g/kg$. Generally These results show that the contamination level of aflatoxins in Herb Medicines consumed in Korea is high compared with the standard in Korea Herb Medicine Code($10\;{\mu}g/kg$ as aflatoxin B1). It is considered that aflatoxin concentration was increased in herb medicines during a storage and drying in herb medicines examined

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.6
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• pp.464-472
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• 2014

The Codex Committee of Contaminants in Food (CCCF) has been discussing a new standard for arsenic (As) in rice since 2010 and a code of practice for the prevention and reduction of As contamination in rice since 2013. Therefore, our current studies focus on setting a maximum level of As in rice and paddy soil by considering bioavailability in the remediation of As contaminated soils. This study aimed to select an appropriate single chemical extractant for evaluating the mobility of As in paddy soil and the bioavailability of As to rice. Nine different extractants, such as deionized water, 0.01 M $Ca(NO_3)_2$, 0.1 M HCl, 0.2 M $C_6H_8O_7$, 0.43 M $HNO_3$, 0.43 M $CH_3COOH$, 0.5 M $KH_2PO_4$, 1 M HCl, and 1 M $NH_4NO_3$ were used in this study. Total As content in soil was also determined after aqua regia digestion. The As extractability of the was in the order of: Aqua regia > 1 M HCl > 0.5 M $KH_2PO_4$ > 0.43 M $HNO_3$ > 0.2 M $C_6H_8O_7$ > 0.1 M HCl > 0.43 M $CH_3COOH$ > deionized water > 1 M $NH_4NO_3$ > 0.01 M $Ca(NO_3)_2$. Correlation between soil extractants and As content in rice was in the order of : deionized water > 0.01 M $Ca(NO_3)_2$ > 0.43 M $CH_3COOH$ > 0.1 M HCl > 0.5 M $KH_2PO_4$ > 1 M $NH_4NO_3$ > 0.2 M $C_6H_8O_7$ > 0.43 M $HNO_3$ > 1M HCl > Aqua regia. BCF (bioconcentration factor) according to extractants was in the order of : 0.01M $Ca(NO_3)_2$ > 1 M $NH_4NO_3$ > deionized water > 0.43 M $CH_3COOH$ > 0.1 M HCl > 0.43 M $HNO_3$ > 0.2 M $C_6H_8O_7$ > 0.5 M $KH_2PO_4$ > 1 M HCl > Aqua regia. Therefore, 0.01 M $Ca(NO_3)_2$ ($r=0.78^{**}$) was proven to have the greatest potential for predicting As bioavailability in soil with higher correlation between As in rice and the extractant.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.904-911
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• 2021

For the safety assessment of microbiological and chemical hazards in dried sea mustard, fifteen samples of dried sea mustards Undaria pinnatifida were purchased from the supermarkets distributed throughout Korea. The contamination levels of total viable bacteria, coliforms, Escherichia coli, and nine pathogenic bacteria [Staphylococcus aureus, Salmonella spp., Listeria monocytogenes, Bacillus cereus, Vibrio spp., Clostridium perfringens, Enterohemorrhagic Escherichia coli (EHEC), Yersinia enterocolitica and Campylobacter jejuni/coli] were quantitatively or qualitatively assessed. Also, the heavy metals (lead, cadmium, total mercury, and inorganic arsenic), and radioactivity (¹³¹I, ¹³⁴CS+¹³⁷CS) were quantitatively assessed. This microbial and chemical analysis was performed using standard methods in Korean food code. The total viable bacteria ranged from 4.3×10² (5.0×10-1.5×10³) CFU/g. Coliforms and E. coli were not detected in all samples (ND, <1 log₁₀ CFU/g). All nine pathogenic bacteria were qualitatively detected as negative. The contamination levels of lead, cadmium, total mercury, and inorganic arsenic were 0.036 (0.015-0.051), 0.117 (0.088-0.156), 0.030 (0.017-0.048), and 0.058 (0.056-0.064) mg/kg, respectively. Radioactivity was also not detected in any sample. The microbial contamination levels determined in the current study may be potentially used as basis for performing microbial risk assessments of dried sea mustards.

• Land and Housing Review
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• v.2 no.4
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• pp.559-568
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• 2011

This study aims at listing up those manufacturing activities sensitive to regional characteristics by analyzing locational hierarchy designed on the urban rank-size rule. This locational hierarchy by manufacturing activities is expected to provide a ground for the proper supply of an industrial complex. The analysis of the locational hierarchy by manufacturing activities can work as a method of observing the characteristics of the distribution of location for each economic activity by analyzing the trend in the change of manufacturing location. Consequently, it can be used to determine the appropriate manufacturing activities for the industrial complex of a particular region. Here, the locational hierarchy is analyzed depending on the base of the basic local government such as Gun(district level) and Si(city level), and manufacturing activities are categorized by Korea Standard Industry Code. Those activities demonstrating growth pattern are Manufacture of Electronic Equipment(KSIC 26), Manufacture of Medical Precision Optical Instruments Watch(KSIC 27), Manufacture of Motor Vehicles (KSIC 30, 31), etc. With proper infrastructures, these activities can be located everywhere. Those sectors on the decline pattern in the locational hierarchy can be summarized as Manufacture of Tobacco Products(KSIC 12), Manufacture of wearing apparel Fur Articles(KSIC 14), etc. Those sectors scattered widely in the locational hierarchy are Manufacture of Food Products(KSIC 10), Manufacture of Coke Petroleum Products(KSIC 19), Manufacture of Chemical Products(KSIC 20), Manufacture of Electronic Equipment(KSIC 26). These particular manufacturing activities can be operated in those regions in a sufficient supply of unskilled workers regardless of proper infrastructures. Those activities that have a tendency to reconcentrate on larger cities are Manufacture of Textiles(KSIC 13), Manufacture of Wearing Apparel Clothing Fur Articles(KSIC 14), Manufacture of Other Transport Equiptmen(KSIC 31). In most cases, these sectors tend to favor their existing agglomerated areas and concentrate around large cities. Therefore, it is inefficient to promote these sectors in small or medium-sized cities or underdeveloped regions. The establishment of developmental strategies of an industrial complex can gain greater competitiveness by observing such characteristics of the locational hierarchy.