• 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.50 no.spc1
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• pp.161-166
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• 2005

Objectives of this study were to select inbred lines which have a good eating quality and desirable segregates during inbreeding of waxy corn. The 64 inbred lines showed a large variance in their kernel shape and weight. 100-kernel weight, pericarp thickness, kernel length, kernel width, and kernel thickness ranged $11.7\~37.3g,\;11\~77{\mu}m,\;5.8\~9.6mm,\;6.5\~10.0mm$, and $4.1\~6.8mm$, respectively. The physicochemical analysis of 64 waxy corn inbred lines showed crude protein, crude fat, free sugar, and amylopectin content ranging $8.7\~15.8\%,\;2.3\~5.8\%,\;1.1\~11.0\%,\;and\;78.5\~93.8\%$, respectively. The texture property analysis of 64 inbred lines by texture analyzer showed a big difference. Gumminess, hardness, and chewiness of 64 inbred lines ranged $91\~383,\;181\~394,\;and\;73\~370$, respectively. The principal component analysis for 14 characteristics related to kernel quality showed that $73.1\%$ of the total variation could be attributed to the first five principal components. Biological meaning of the principal component was explained clearly by the correlation coefficient between principal components and characters. The first principal component appeared to correspond to small kernel and bad eating quality, The second principal component appeared to correspond to large kernel and good eating quality. The 64 inbred lines were classified into 8 groups by the cluster analysis using the first and second principal component. Among the groups, group VII and VIII included inbred lines with good eating quality that had thin pericarp thickness, low protein content, large kernel, and soft tenderness.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.1
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• pp.76-87
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• 2014

Chlorophyll a in seawater which is an indicator of phytoplankton biomass and primary production is determined by High Performance Liquid Chromatography (HPLC), Fluorometry and Spectrophotometry. In this study, various methods for chlorophyll a determination in seawater are compared using in situ seawater samples from Korean seas. Three inter-laboratory comparison campaigns were carried out using chlorophyll a standard samples (R0) and in situ seawater samples, collected from the East China Sea (R1) and the East Sea (R2). 6 laboratories by HPLC methods, 4 laboratories by fluorometry, and 3 laboratories by spectrophotometry participated. Precisions, defined as the coefficient of variation (CV) were within 9% in standard samples, 0.8~20% (average: 6.1%) in R1, 4~21% (average: 13.2%) in R2. Discrepancy in three methods was approximately 20% within the range of the sample homogeneity intended the laboratory precision (R1: 8%, R2: 15%). The discrepancy in laboratories was greater than the discrepancy in methods. The chlorophyll a concentrations can be produced within 20% discrepancy in spite of using different methods. It is recommended to consider this 20% discrepancy when using the chlorophyll a data produced by different laboratories and different methods.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• Journal of Korean Society of Forest Science
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• v.46 no.1
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• pp.29-43
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• 1980

The sampling methods selected for this area was (1) Simple random sampling (2) Systematic sampling and (3) Sub-sampling. For the calculation of the number of sampling plot, 10 % coefficient of variation was adapted. As a result, 57 plots each for simple random sampling and systematic sampling was calculated. In the sub-sampling method, however, total of 40 plots, which were consisted of 5 Blocks, secondary 4 major units and tertiary 2 minor units, were examined. The reuslts obtained are summarized as follows : 1. The rate of expected error was 9.24% for simple random sampling, 8.36% for systematic sampling and 7.54% for sub-sampling, respectively. Therefore, the sub-sampling was proved to be the most accurate method among the test. 2. The volume calculated by each sampling method was compared to the volume of all stand. The rate of expected error was also lowest in the sub-sampling (0.39%), followed by systematic sampling (4.18%) and simple random sampling (7.92%). 3. Comparing the various reuslts and analysis of these results, the sub-sampling was regarded as the most rapid and economical method because this method had not only the least number of plots but also the least expected error among the tested sampling methods Therefore the sub-sampling is proved to be an ideal sampling method for forest survey.

• Korean Journal of Medicinal Crop Science
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• v.5 no.3
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• pp.177-185
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• 1997

Twenty-four major ecological and physiolosical characters of the 54 accessions of taro(Colocasia antiquorum) were observed in the growing seasons of 1995 and 1996 in $Ch{\breve{o}}nju$, Korea. The average days to emergence of the 54 accessions were 21.7 and the accession which had the shortest days to emergence was Kurye #2. Petiole color of most accessions was green, except $Ich{\breve{o}}n$ #1, Iri #1, Puan #1 and Taiwan #1 which had purple petioles. All the accessions had cormels except Taiwan #1 which had long runners without cormels. Average yield of the accessions was 3,719 kg/10a and total carmel weight, average carmel number, average carmel and average corm weight were 787g/plant, 39.2/plant, 20.3g/cormel, and 263.6g/plant, respectively. Accessions $Ch{\breve{o}}ngju$ #1 and Wanju #1 showed superiority in the three important characters, total carmel weight/plant, average carmel weight, and corm weight. Multivariate analysis for the 24 characters indicated that petiole color and carmel type had relatively higher coefficient of variation, 56.8 and 44.4 %, respectively. Fifty four taro accessions could be classified into 11 groups with D(${\sqrt{D^{2}}$) value of 110 on the basis of phenotypical characteristics. Most accessions were inclued in Group II. The Group I in which Taiwan #1 was included was genetically the most distant from the other groups. Accessions with purple petioles were grouped into the three different subgroups in which green petiole accessions were not included, indicating high dissimilarity between the different petiole color accessions. All the accessions grouped into the Group VIII, $Ch{\breve{o}}ngju$ #1, Wanju #1, Wanju #3, and $Taech{\breve{o}}n$ #2, had higher bioogical yield. Some accessions collected from the same district showed a high dissimilarity by being classified into the different subgroups.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.247-261
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• 2018

The purpose of this study is to evaluate the groundwater level behavior of Geum river basin ($9,645.5km^2$) under future climate change scenario projection periods (2020s: 2010~2039, 2050s: 2040~2069, 2080s: 2070~2099) using SWAT (Soil and Water Assessment Tool). Before future evaluation, the SWAT was calibrated and validated using 11 years (2005~2015) daily multi-purpose dam inflow at 2 locations (DCD, YDD), ground water level data at 5 locations (JSJS, OCCS, BEMR, CASS, BYBY), and three years (2012~2015) daily multi-function weir inflow at 3 locations (SJW, GJW, BJW). For the two dam inflow and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.57~0.67 and 0.87~0.94, and the coefficient of determination ($R^2$) was 0.69~0.73 and 0.63~0.73 respectively. For the three weir inflow and storage, the NSE was 0.68~0.70 and 0.94~0.99, and the $R^2$ was 0.83~0.86 and 0.48~0.61 respectively. The average $R^2$ for groundwater level was from 0.53 to 0.61. Under the future temperature increase of $4.3^{\circ}C$ and precipitation increase of 6.9% in 2080s (2070~2099) based on the historical periods (1976~2005) from HadGEM3-RA RCP 8.5 scenario, the future groundwater level shows decrease of -13.0 cm, -5.0 cm, -9.0 cm at 3 upstream locations (JSJS, OCCS, BEMR) and increase of +3.0 cm, +1.0 cm at 2 downstream locations (CASS, BYBY) respectively. The future groundwater level was directly affected by the groundwater recharge by the future seasonal spatial variation of rainfall in the watershed.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.12-18
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• 2004

Ofloxacin, norfloxacin, ciprofloxacin, and enrofloxacin in chicken muscle were seperated by liquid extraction and determined with high performance liquid chromatography (HPLC) with fluorescence detector. Analysis was carried out using following conditions; Cl8 column (250${\times}$4.6 mm i.d. 5 ${\mu}{\textrm}{m}$ particle size), mobile phase composed of D.W. (containing 0.4% triethylamine and phospholic acid): methanol : acetonitrile (800:100:100, v/v/v), isocratic pump at a flow rate of 1.0 $m\ell$/min and 50 ${mu}ell$ of injection volume, fluorescence detector with EX278 nm/EM.456 nm. The calibration curves of four fluoroquinolones showed linearity (${\gamma}$$^2$$\geq$0.999) at concenration range of 0.025-0.6 $\mu\textrm{g}$/ml. The recoveries in fortified chicken muscle represented more than 80% with low coefficient of variation (〈10%) for concentration range of four fluoroquinolones. The detection limits for ofloxacin, norfloxacin, ciprofloxacin, and enrofloxacin were 23.5, 3.4, 3.0 and 2.5 ng/g in chicken muscle, respectively. We also monitored fluoroquinolones residue in muscle of chickens (broiler 1:227, Korean native chicken 219, laying chicken 77) using EEC-4-plate screening and HPLC conformation methods. Ten(broiler 5, Korean native chicken 5) out of the fifteen samples which were positively detected by EEC-plate screening method from 1,523 chicken meat were confirmed with ciprofloxacin and enrofloxacin by HPLC. The ranges of residual concentration were 0-0.12 ppm for ciprofloxacin and 0.01-6.79 ppm for enrofloxacin. In conclusion, our method could be applied effectively to determine four fluoroquinolones residues in chicken meat, and further survey for fluoroquinolones residue in chicken meat are needed for more effective control of fluoroquinolones used in livestock.

• Journal of Bio-Environment Control
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• v.16 no.4
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• pp.395-406
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• 2007

The twenty seven wrap-up vegetables (13 Compositae, 14 Brassicaceae) and seven herbs (6 Labiatae, 1 Umbelliferae) were cultivated with a deep flow technique (DFT) hydroponic beds and treated with 3 levels of nutrient solution concentrations of 1.2, 2.4, and $3.6dS{\cdot}m^{-1}$ in summer and autumn season. The pH and electrical conductivity (EC) change of nutrient solution, fresh weight, and mineral contents of plants were investigated. The pH was maintained lower in high electrical conductivity (EC) treatment and in summer than autumn. EC of nutrient solution in EC $3.6dS{\cdot}m^{-1}$ treatment increased up to $4.8dS{\cdot}m^{-1}$ during the growing period in summer season. The growth of tested plants showed high variations by plant species and nutrient solution concentrations. The coefficient variation (CV) of the shoot fresh weight of plants was higher in summer than autumn. The growth of Compostiae and herbs was better at EC $1.2dS{\cdot}m^{-1}$, and 14 Brassicaceae was better at EC $2.4dS{\cdot}m^{-1}$ in summer. In autumn, the growth was better at EC $2.4dS{\cdot}m^{-1}$ in all plants except kale 'TBC F1' and red rape 'honchaetae'. In mineral contents, total nitrogen and potassium were higher in autumn than summer. Total nitrogen, potassium, calcium, magnesium were higher in Brassicaceae than others. Iron and manganese, however, were higher in Compositae. As the results, this study suggests that mixed planting of 27 wrap-up vegetables and 7 herbs in DFT hydroponics in two seasons was possible and EC $1.2dS{\cdot}m^{-1}$ in summer and EC $2.4dS{\cdot}m^{-1}$ in autumn be recommended as for the nutrient solution concentration to produce them safely year round.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.127-135
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• 2023

This study aimed to develop biomass allometric equations and estimate carbon emission factors, such as the wood density, biomass-expansion factor, and root-to-shoot ratio, for Platanus occidentalis and Metasequoia glyptostroboides planted in urban areas. Twenty M. glyptostroboides and 25 P. occidentalis trees were harvested, and the dry weights and stem volumes of stems, branches, leaves, and roots (>5 mm) were measured. The wood densities of M. glyptostroboides and P. occidentalis were 0.293 ± 0.008 g cm^-3 and 0.509 ± 0.018 g cm^-3, and the biomass-expansion factors were 1.738 ± 0.031 and 1.561 ± 0.035. The root-to-shoot ratios were 0.446 ± 0.009 and 0.402 ± 0.012. The uncertainty tests (coefficient of variation, %) gave 2.8% and 3.5% values for wood density, 1.8% and 2.3% for biomass-expansion factor, and 2.1% and 2.9% for root-to-shoot ratio, respectively. Among the developed allometric equations, Model I using the diameter at breast height (DBH) was suitable. The allometric equations of M. glyptostroboides and P. occidentalis above ground were y = 1.679 (DBH)^1.315 and y = 0.505 (DBH)^1.896, and the allometric equations of the root and total were y = 0.746 (DBH)^1.315, y = 0.301 (DBH)^1.751, y = 2.422 (DBH)^1.316, and y = 0.787 (DBH)^1.858. If the carbon-emission factors of this study and biomass allometric equations of the three developed models are used to estimate the carbon storage and biomass of urban forests, errors caused by not considering the use of fixed factors and the environmental differences can be reduced.