• Korean Journal of Soil Science and Fertilizer
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• v.12 no.1
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• pp.15-23
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• 1979

In the first paper of the series the five soil fertility factors were evaluated by means of principal component analysis and varimax method. They are interpreted as representing, 1) skeletal available phosporus status, 2) organnic matter status, 3) salt status 4) base status, and 5) free oxide status. In order to resynthesize such fragmented information for the overall soil fertility evaluation, the method of multiple regression analysis was adopted, using the five factor scores and yield data for Korean paddy soils as independent and dependent variables respectively. As test of linear models with different combinations of independent variables the results of t-test of regression coefficient were revealed that the organic matter status (FII) has no relevance to the yield of paddy and that the free oxides and salt supply has by it self only an insignificant contribution to the yield. The multiple correlation coefficient (R) revealed its multiple regression analysis was as low as 0.43. Introduction of quadratic terms to the linear model bettered the result. Thus multiple correlation coefficient (R) was increased as 0.59. Therefore, a coefficient of determination 0.35 was obtained by a quadratic model with interaction terms among the five fertility constituents. Generally we think that the fertility factor has more contribution to raise the rice yield in paddy and that the failure of yield prediction by fertility factor scores was caused by one of follows; 1) the roughness of the yield inspection, and 2) missextraction of fertility constituents. The second step in this study, assuming that the residuals by multiple regression analysis were due to factors other than soil fertility, we can now proceed to predicting the yield from the field characters with the classified fertility groups by means of Hayashi's theory of quantification No. 1. Such variables as fertility groups (FTYG), water availability (WATER), soil drainage (DRNG), climatic zone (CLIZ), surface soil's stickiness (STCKT), surface soil's dry consistence (DCNST), and surface soil's texture (FTEXT) are taken up as the explanatory variables. The quantification appears reasonable; the well to extremely well in soil drainage, very sticky of surface soil, inefficiency in water availability, coarse texture, and very hard to extremely hard dry consistence in soil are detrimental to the rice yield. The R was as high as 0.90 for the set of variables. But the given explanatory variables in this study were not quite effective in explaining rice yield. The method developed seems to be promising only if properly collected data are available. Conditions that should be satisfied in the yield inspection obtained from common cultivator for the purpose of deriving a prediction equation were put forward.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.312-318
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• 2010

This study was carried out to develop and test a prototype program that recommends the nitrogen topdressing rate using the color digital camera image taken from rice field at panicle initiation stage (PIS). This program comprises four models to estimate shoot N content (PNup) by color digital image analysis, shoot N accumulation from PIS to maturity (PHNup), yield, and protein content of rice. The models were formulated using data set from N rate experiments in 2008. PNup was found to be estimated by non-linear regression model using canopy cover and normalized green values calculated from color digital image analysis as predictor variables. PHNup could be predicted by quadratic regression model from PNup and N fertilization rate at panicle initiation stage with $R^2$ of 0.923. Yield and protein content of rice could also be predicted by quadratic regression models using PNup and PHNup as predictor variables with $R^2$ of 0.859 and 0.804, respectively. The performance of the program integrating the above models to recommend N topdressing rate at PIS was field-tested in 2009. N topdressing rate prescribed for the target protein content of 6.0% by the program were lower by about 30% compared to the fixed rate of 30% that is recommended conventionally as the split application rate of N fertilizer at PIS, while rice yield in the plots top-dressed with the prescribed N rate were not different from those of the plots top-dressed with the fixed N rates of 30% and showed a little lower or similar protein content of rice as well. And coefficients of variation in rice yield and quality parameters were reduced substantially by the prescribed N topdressing. These results indicate that the N rate recommendation using the analysis of color digital camera image is promising to be applied for precise management of N fertilization. However, for the universal and practical application the component models of the program are needed to be improved so as to be applicable to the diverse edaphic and climatic condition.

• Journal of the Korean Regional Science Association
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• v.34 no.2
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• pp.3-19
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• 2018

The objective of this study is to observe the efficiency of clinical performance on the supply and demand of medical resources in Korea. For the empirical analysis, we constructed the dataset on age standardized mortality rate, the number of physician, specialist, surgery, medical institution, ratio of general hospitals of 16 provinces in Korea from 2006 to 2013. The panel probability frontier model is employed as an analysis method and considered heteroscedasticity and autocorrelation of the error in panel data. In addition, the demographic and socioeconomic characteristics of the 16 provinces, unemployment rate, elderly population ratio, GRDP per capita, and ratio of hospitals in comparison to the general hospitals are used to find the effect on the technical efficiency of clinical performance on supply and demand of medical resources. The results are as follows. First, for the clinical performance, the supply side of human resources such as doctors and specialists and the demand side factors such as chronic illness clinic per unit population have a significant influence, respectively. Second, the technical efficiency of clinical performance on the supply and demand of medical resources of each input component was 59-70% in terms of clinical efficiency in each region. Third. estimates of technical efficiency of inputs that affect clinical performance showed a slight increase in all regions during the analysis period, but the increase trend decreased slightly. Fourth, the ratio of the elderly population and GRDP per capita have a positive influence on the technical efficiency of clinical performance on the supply and demand of medical resources. The difference of each efficiency by region is due to the regional differences of the input medical resources and the combination of them and the demographic and socioeconomic characteristics of the region. It is understood that the differences in technological efficiency due to the complexity of supply and demand of medical resources, demographic structure and economic difference affecting clinical performance by region are different.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.1
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• pp.66-75
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• 2014

This study aims to understand environmental factors that determine spatial distribution of macrozoobenthic community in the southern area (ca 100-500 m depth) of East Sea, Korea, known as a candidate site for carbon storage under the seabed. From sixteen locations sampled in the summer of 2012, a total of 158 species were identified, showing density of $843indiv/m^2$ and biomass of $26.2g\;WW/m^2$, with increasing faunal density towards biologically higher diverse locations. Principal component analysis showed that a total of 33 environmental parameters were reduced to three principal components (PC), indicating sediment, bottom water, and depth, respectively. As sand content was increasing, number of species increased but biomass decreased. Six dominant species including two bivalve species favored high concentrations of ${\Omega}$ aragonite and ${\Omega}$ calcite, indicating that the corresponding species can be severely damaged by ocean acidification or $CO_2$ effluent. Cluaster analysis based on more than 1% density dominant species classified the entire study area into four faunal assemblage (location groups), which were delineated by characteristic species, including (A) Ampelisca miharaensis, (B) Edwardsioides japonica, (C) Maldane cristata, (D) Spiophanes kroeyeri, and clearly separated in terms of geography, bottom water and sediment environment. Overall, a discriminant function model was developed to predict four faunal assemblages from five simply-measured environmental variables (depth, sand content in sediment, temperature, salinity and pH in bottom water) with 100% accuracy, implying that benthic faunal assemablages are closed linked to certain combinations of abiotic factors.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• Tuberculosis and Respiratory Diseases
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• v.60 no.6
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• pp.663-672
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• 2006

Background: $PM_{10}$(Particulate matter with a diameter ($<10{\mu}m$), which is characterized by different environmental conditions, is a complex mixture of organic and inorganic compounds. The Asian dust event caused by meteorological phenomena can also produce unique particulate matter in affected areas. This study investigated the cytokine produced by A549 epithelial cells exposed to particles collected during both the Asian dust pfenomenon and ambient air particles in a non-dusty period. Method: Air samples were collected using a high volume air sampler(Sibata Model HV500F) with an air flow at $500{\ell}/min$ for at least 6 hours. The cytokine messenger RNA(mRNA) was measured using a reverse transcriptase polymerase chain reaction(RT-PCR). The A549 cells were exposed to 10 to $500{\mu}g/m{\ell}$ of a suspension containing $PM_{10}$ for 24 hours. Each was compared with those in the non-exposed control cells. Result: The mRNA levels of interleukin(IL)-$1{\alpha}$, $IL-I{\beta}$, IL-8, and the granulocyte macrophage colony stimulating factor(GM-CSF) increased after veing exposed to $PM_{10}$ in the ambient air particles, compared with those in the non-exposed control cells. The increase in $IL-1{\alpha}$ and IL-8 were dose dependent at a $PM_{10}$ concentration between $100{\mu}g/m{\ell}$ and $500{\mu}g/m{\ell}$. The mRNA level of IL-8 in the A549 epithelial cells was higher during the in the Asian dust period($500{\mu}g/m{\ell}$) than during the non dust period. Conclusion: A549 cells exposed to the $PM_{10}$ collected during the Asian dust period produce more proinflammatory cytokine than during non-dusty period. This cytokine enhances the local inflammatory response in the airways and can also contribute to the systemic component of this inflammatory process.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.6
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• pp.729-738
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• 1997

To estimate the change in rice productivity around lake Juam due to construction of artificial lake, growth, yield components and yield of rice were measured at different locations around lake Juam for three years from 1994 to 1996. Automated weather stations(AWS) were installed nearby the experimental paddy fields, and daily maximum, average and minimum temperature, solar radiation, relative humidity, and precipitation were measured for the whole growing period of rice. Plant height, number of tillers, leaf area and shoot dry weight per hill were observed from 8 to 10 times in the interval of 7 days after transplanting. Yield and yield components of rice were observed at the harvest time. Simulation model of rice productivity used in the study was SIMRIW developed by Horie. The observed data of rice at 5 locations in 1994, 3 locations in 1995 and 4 locations in 1996 were inputted in the model to estimate the unknown parameters. Comparisons between observed and predicted values of shoot dry weights, leaf area indices, and rough rice yield were fairly well, so that SIMRIW appeared to predict relatively well the variations in productivity due to variations of climatic factors in the habitat. Climatic elements prior to as well as posterior to dam construction were generated at six locatons around lake Juam for thirty years by the method of Pickering et al. Climatic elements simulated in the study were daily maximum and minimum temperature, and amount of daily solar radiation. The change in rice productivity around lake Juam due to dam construction were estimated by inputting the generated climatic elements into SIMRIW. Average daily maximum temperature after dam construction appeared to be more or less lower than that before dam construction, while average daily minimum temperature became higher after dam construction. Average amount of daily solar radiation became lower with 0.9 MJ $d^{-1}$ after dam construction. As a result of simulation, the average productivity of habitats around lake Juam decreased about 5.6% by the construction of dam.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.99-120
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• 1997

Solar radiation is scattered and absorbed atmospheric compositions in the atmosphere before it reaches the surface and, then after reflected at the surface, until it reaches the satellite sensor. Therefore, consideration of the radiative transfer through the atmosphere is essential for the quantitave analysis of the satellite sensed data, specially at shortwave region. This study examined a feasibility of using radiative transfer code for estimating the atmospheric effects on satellite remote sensing data. To do this, the flux simulated by LOWTRAN7 is compared with CAGEX data in shortwave region. The CAGEX (CERES/ARM/GEWEX Experiment) data provides a dataset of (1) atmospheric soundings, aerosol optical depth and albedo, (2) ARM(Aerosol Radiation Measurement) radiation flux measured by pyrgeometers, pyrheliometer and shadow pyranometer and (3) broadband shortwave flux simulated by Fu-Liou's radiative transfer code. To simulate aerosol effect using the radiative transfer model, the aerosol optical characteristics were extracted from observed aerosol column optical depth, Spinhirne's experimental vertical distribution of scattering coefficient and D'Almeida's statistical atmospheric aerosols radiative characteristics. Simulation of LOWTRAN7 are performed on 31 sample of completely clear days. LOWTRAN's result and CAGEX data are compared on upward, downward direct, downward diffuse solar flux at the surface and upward solar flux at the top of the atmosphere(TOA). The standard errors in LOWTRAN7 simulation of the above components are within 5% except for the downward diffuse solar flux at the surface(6.9%). The results show that a large part of error in LOWTRAN7 flux simulation appeared in the diffuse component due to scattering mainly by atmispheric aerosol. For improving the accuracy of radiative transfer simulation by model, there is a need to provide better information about the radiative charateristrics of atmospheric aerosols.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• Journal of Life Science
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• v.32 no.11
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• pp.872-881
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• 2022

In this study, we optimized the composition of the indole-3-acetic acid (IAA) production medium using response surface methodology on Pantoea agglomerans SRCM 119864 isolated from soil. IAA-producing P. aglomerans SRCM 119864 was identified by 16S rRNA gene sequencing. There are 11 intermediate components known to affect IAA production, hence the effect of each component on IAA production was investigated using a Plackett-Burman design (PBD). Based on the PBD, sucrose, tryptone, and sodium chloride were selected as the main factors that enhanced the IAA production at optimal L-tryptophan concentration. The predicted maximum IAA production (64.34 mg/l) was obtained for a concentration of sucrose of 13.38 g/l, of tryptone of 18.34 g/l, of sodium chloride of 9.71 g/l, and of L-tryptophan of 6.25 g/l using a the hybrid design experimental model. In the experiment, the nutrient broth medium supplemented with 0.1% L-tryptophan as the basal medium produced 45.24 mg/l of IAA, whereas the optimized medium produced 65.40 mg/l of IAA, resulting in a 44.56% increase in efficiency. It was confirmed that the IAA production of the designed optimal composition medium was very similar to the predicted IAA production. The statistical significance and suitability of the experimental model were verified through analysis of variance (ANOVA). Therefore, in this study, we determined the optimal growth medium concentration for the maximum production of IAA, which can contribute to sustainable agriculture and increase crop yield.