• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.1
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• pp.1-12
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• 2004

The summer distribution of $Cha-{alpha}$ and physical processes for simulating outbreak region of red tide were estimated by the Eco-Hydrodynamic model in Chinhae Bay. As a result of simulation of surface residual currents, the southward flow come in contact with the northward flow at the inlet and western part of bay in case of windlessness and below wind velocity 2 m/sec. As wind velocity increases, the velocity and direction of currents were fairly shifted. The predicted concentration of $Cha-{alpha}$ exceeded 20 mg/㎥ in Masan and Haengam Bays, and most regions were over 10 mg/㎥, which meant the possibility of red tide outbreak. From the results of the contributed physical processes to $Cha-{alpha}$, accumulation sites were distributed at the northern part of Kadok channel, around the Chilcheon island, the western part of Kajo island and some area of Chindong Bay. On the other hand, inner parts of the study area such as Masan Bay were estimated as the sites of strong algal activities. Masan and Haengam Bay are considered as the initial outbreak region of red tide by the modeling and observed data, and then red tide expanded to other areas such as physical accumulation region and western inner bay, as depending on environmental variation. The increase of wind velocity led to decrease of $Cha-{alpha}$ and enlargement of accumulation region. The variation of intensity of radiation and sunshine duration caused to rapidly fluctuation of $Cha-{alpha}$: however, it was not largely affected by the variation of pollutant loads from the land only.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.7
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• pp.1331-1343
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• 2000

Through the integration of USLE and GIS, the methodology to estimate the soil loss was developed, and applicated to the Sacheon river in Gangrung. Using GIS, spatial analysis such as watershed boundary determination, flow routing. slope steepness calculation was done. Spatial information from the GIS application was given for each grid. With soil and land use map, information about soil classification and land use was given for each grid too. Based upon these data, thematic maps about the factors of USLE were made. We estimated the soil loss by overlaying the thematic maps. In this manner, we can assess the degree of soil loss for each grid using GIS. Annual average soil loss of Sacheon river watershed is 1.36 ton/ha/yr. Soil loss in forest, dry field, and paddy field is 0.15 ton/ha/yr, 27.04 ton/ha/yr, 0.78 ton/ha/yr respectively. The area of dry field, which is 4% of total area, is $2.4km^2$. But total soil loss of dry field is 6561 ton/yr, and it occupies 84.9 % of total soil loss eroded in Sacheon river watershed. Comparing with the 11.2 ton/ha/yr of an average soil loss tolerance for cropland, provision for the soil loss in dry field is necessary. Run-off and water quality of Sacheon river were measured two times in flood season: from July 24, 1998 to July 28 and from September 29 to October 1. As the run-off of the river increased, SS, TN, TP concentrations and pollutant loadings increased. SS, TN, TP loads of Sacheon river discharged during the 2 heavy rains were 21%, 39%, and 19% of the total pollutant loadings generated in the Sacheon river watershed for one year. We can see that much pollutants are discharged in short period of flood season.

• Journal of Animal Science and Technology
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• v.53 no.1
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• pp.1-6
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• 2011

This simulation study was performed to investigate the accuracy of the estimated breeding value by using genomic information (GEBV) by way of Bayesian framework. Genomic information by way of single nucleotide polymorphism (SNP) from a chromosome with length of 100cM were simulated with different marker distance (0.1cM, 0.5cM), heritabilities (0.1, 0.5) and half sibs families (20 heads, 4 heads). For generating the simulated population in which animals were inferred to genomic polymorphism, we assumed that the number of quantitative trait loci (QTL) were equal with the number of no effect markers. The positions of markers and QTLs were located with even and scatter distances, respectively. The accuracies of estimated breeding values by way of indicating correlations between true and estimated breeding values were compared on several cases of marker distances, heritabilities and family sizes. The accuracies of breeding values on animals only having genomic information were 0.87 and 0.81 in marker distances of 0.1cM and 0.5cM, respectively. These accuracies were shown to be influenced by heritabilities (0.87 at $h^2$ =0.10, 0.94 at $h^2$ =0.50). According to half sibs' family size, these accuracies were 0.87 and 0.84 in family size of 20 and 4, respectively. As half sibs family size is high, accuracy of breeding appeared high. Based on the results of this study it is concluded that the amount of marker information, heritability and family size would influence the accuracy of the estimated breeding values in genomic selection methodology for animal breeding.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.1
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• pp.56-62
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• 2020

The meteorological ecology of a soybean variety (Glycine max Merrill) and its characteristics are important factors in selecting soybean variety suitable for the environment. This experiment was conducted to estimate the meteorological- ecological characteristics of soybean for 27 crop cultivation regions in North Korea. The meteorological ecology of each region was determined by the last harvest date and the maximum growth day determined using the daily minimum temperature of the region. The soybean meteorological group for 27 regions in North Korea was classified by eight groups. The last harvest date of group I, the south-west and south-east areas, was from October 21 to 29, which was the latest harvest date among the eight groups. It became shorter toward the central inland and mountainous areas of group IV, and it ranged from September 18 to October 2. The maximum number of growth days was 153~160 days in group I, and 100~111 days in group IV-3, the northernmost area of the east coast. Assuming total growth days as 110 days, the ranges of last flowering dates (and the day length) of group I, II, III, and IV were August 12~19 (day length of 13.5~13.8 h), August 2~6 (14-14.2 h), July 27~August 2 (14.2~14.4 h), and July 10~22 (14.5~14.8 h), respectively. The accumulative temperature of 110 growth days was above 2,400℃ in group II-1, the south to north area of the west inland, and above 2,300℃ in all regions except Cheongjin, Seonbong, and Jung-gang. The accumulative temperature calculated based on the maximum growth day was above 3,000℃ in group I and II-1 and above 2,500℃ in group II-2, the central area of the east coast, III-1, the central inland area, and IV-1, the central inland mountain area.

• Geophysics and Geophysical Exploration
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• v.10 no.3
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• pp.173-182
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• 2007

It is well known that manganese nodules enriched with valuable metals are abundantly distributed in the abyssal plain area in the Clarion-Clipperton (C-C) fracture zone of the northeast Pacific. Previous studies using deep-sea camera (DSC) system reported different observations about the relation of seafloor topographic change and nodule abundance, and they were sometimes contradictory. Moreover, proper foundation on the estimation of DSC underwater position, was not introduced clearly. The variability of the mining condition of manganese nodule according to seafloor topography was examined in the Korea Deep Ocean Study (KODOS) area, located in the C-C zone. In this paper, it is suggested that the utilization of deep towing system such as DSC is very useful approach to whom are interested in analysing the distributional characteristics of manganese nodule filed and in selecting promising minable area. To this purpose, nodule abundance and detailed bathymetry were acquired using deep-sea camera system and multi-beam echo sounder, respectively on the seamount free abyssal hill area of southern part ($132^{\circ}10'W$, $9^{\circ}45'N$) in KODOS regime. Some reasonable assumptions were introduced to enhance the accuracy of estimated DSC sampling position. The accuracy in the result of estimated underwater position was verified indirectly through the comparison of measured abundances on the crossing point of neighboring DSC tracks. From the recorded seafloor images, not only nodules and sediments but cracks and cliffs could be also found frequently. The positions of these probable unminable area were calculated by use of the recorded time being encountered with them from the seafloor images of DSC. The results suggest that the unminable areas are mostly distributed on the slope sides and hill tops, where nodule collector can not travel over.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.73-85
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• 1999

This study was conducted to reveal the characteristics of the early growth by locality for Korean white pine planted in Gapyung and Kwangju, Kyunggi-Do and Youngdong, Choongchungbuk-Do. The effects of local climatic conditions as one of environmental factors on the growth were also analyzed. For this, several stand variables such as number of trees survived, mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, periodic annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique, for the estimation of local climatic conditions, which makes use of empirical relationships between the topography and the weather in study areas was applied to produce reasonable estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine over remote land area where routine observations are rare. From these monthly estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc. which affect the tree growth, were computed for each locality. The periodic annual increments were then correlated with and regressed on the weather variables to examine effects of local weather conditions on the growth. Gapyung area provided the best conditions for the growth of Korean white pine in the early stage and Kwangju area ranked second. On the other hand, the growth pattern in Youngdong ranked last overall as expected. It is also found that the local growth patterns of Korean white pine in juvenile stage were affected by typical weather conditions. The conditions such as low temperature, high relative humidity, and large amount of precipitation provide favorable environment for the growth of Korean white pine. Especially, the diameter growth, basal area growth, and volume growth are mainly influenced by the amount of precipitation. However, it is proved that the height growth is affected by both the precipitation and temperature.

• Korean Journal of Medicinal Crop Science
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• v.2 no.1
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• pp.7-13
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• 1994

This study was conducted to investigate the relationships between yearly variations of climatic factors and yearly variations of productivity in Alisma plantago L. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were collected from the Statistical Year Book of Seungju province, Reserach Report of Seungju Extension Station of Rural Development Administration, and farmers for 10 years from 1983 to 1992. The meteorological data gathered at the Seungju Weather Station for the same period were used to find out the relationships between climatic factors and productivity. Yearly variation of the amount of precipitation in October and the minimum temperature in November were large with coefficients of variation(C.V.) of 106.44, 144.08%, respectively, but the variation of the average temperature, maximum temperature, minimum temperature from July to September were relatively small. Fresh weight and dry weight of roots vary greatly with C. V. of 30.62, 31.85%, respectivly. Plant height and stem length show more or less small C. V. of 5.51, 6. 26%, respectively and leaf width, leaf length, number of stems and root diameter show still less variation. Correlation coefficients between maximum temperature in November and plant height, stem diamter, number of stems, root diamter and dry weight of roots are positively significant at the 5% level. There are high signficant positive correlations observed, between yield and yield components. The maximum temperature would be used as a predictive variable for the estimation of dry weight of roots and number of stems. Simple linear regression equations by the least square method are estimated for number of stems $(Y_1)$ and the maximum temperature in November(X) as $Y_1=4.7114+0.5333\;X\;(R^2=0.4410)$, and for dry weight of roots$(Y_2)$ and the maximum temperature in November(X) as $Y_2=55.0405+14.3233\;X\;(R^2=0.4511)$

• Journal of agriculture & life science
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• v.44 no.5
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• pp.55-64
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• 2010

This study was conducted to estimate genetic parameters for reproductive traits using multivariate animal models in Yorkshire breed. For the study, 4,989 records for litter traits collected between the year 2001 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as farrowing year, parity, weaning to estrus interval (WEI), and suckling period were statistically significant (p<0.05), but farrowing season was not significant, for reproductive traits. The estimates genetic correlations and phenotypic correlations in total number of born and number of suckling, was shown to highly correlated. The genetic correlations were higher than phenotypic correlation. The estimates of heritabilities for reproductive traits, considering permanent environment effects (PE) were much lower than those obtained when permanent environment effects were not considered (NPE) in the model. The estimates of heritabilities were 0.240 and 0.076 for total number of born and 0.187 and 0.096 for number of suckling in NPE, and PE, respectively. These results itivcate that PE should be considered in the statistical mode to estimate more acco ate breeding values.

• Journal of Life Science
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• v.31 no.9
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• pp.840-848
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• 2021

This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.