• Korean Journal of Food Science and Technology
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• v.45 no.3
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• pp.285-292
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• 2013

This study was carried out to validate the safety of ametoctradin residues in agricultural commodities by developing an official analysis method. An analytical method was developed and validated using HPLC-PDA detectors. The samples were extracted with methanol, subsequently partitioned with dichloromethane and purified with florisil column chromatograph using acetone/hexane (30/70, v/v) as solvent. The method was validated by using grape, hulled rice, mandarin, and potato spiked with ametoctradin at 0.05 and 5.0 mg/kg, and pepper at 0.05 and 2.0 mg/kg. Average recoveries were 76-114.8% with relative standard deviation less than 10%, and the limit of detection and limit of quantification were 0.0125 and 0.05 mg/kg, respectively. The result of recoveries and overall coefficient of variation of the laboratory results from Gwangju regional Food and Drug Administration (FDA) and Daejeon regional FDA was accorded with Codex Alimentarius Commission Guideline (CAC/GL 40). Based on these results, this method was found to be appropriate for ametoctradin residue determination and can be used as the official method of analysis.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.2
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• pp.3-6
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• 2012

Purpose : Samsung medical ceter shall find a cause of the interference factor and suggest a solution for it. Materials and Methods : A sample of $^{18}F$-FDG, radioactive pharmaceuticals produced by TRACERlab MX and FASTlab synthesizer. Gel-clot method uses Positive control tube and single test tube. Kinetic chromogenic method uses ENDOSAFE-PTS produced by Charles River. Results : According to Gel clot method of Endotoxin Tests at FASTlab, both turbidity and viscosity increased at 40-fold dilution and Gel clot was detected. In case of TRACERlab MX, Gel clot was detected in most of samples but intermittently not in a few of them. When using ENDOSAFE-PTS, sample CV (Coefficient of Variation) of FASTlab is 0% at all dilution rates whereas spike CV is 0% at 1-fold dilution, 0~35% at 10-fold, 3.6~12.9% at 20-fold, 5.2~7.1% at 30-fold, 1.1~17.4% at 40-fold, spike recovery; 0% at one-fold, 25 ~ 58% at 10-fold, 50 ~ 86% at 20-fold, 70~92% at 30-fold, and 75~120% at 40-fold. Sample CV of TRACERlab MX, is 0% at all dilution rates whereas spike CV is 1.4~4.8% at one-fold dilution, 0.6~19.9% at 10-fold, spike recovery; 35~72% at one-fold dilution and 77~107% at 10-fold. Conclusion : Gel clot does not seem to occur probably to H3PO4 which engages in bonding with Mg2+ion contributing gelation inside PCT. Dilution which is identical to reducing the amount of H3PO4, could remove interfering effects accordingly. Spike recovery was obtained within 70~150% - recommended values of supplier - at 40-fold dilution even in kinetic chromogenic method.

• 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.