Although the dominant land use at the Imha-dam watershed is forest areas, soil erosion has been increasing because of intensive agricultural activities performed at the fields located along the stream for easy-access to water supply and relatively favorable topography. In addition, steep topography at the Imha-dam watershed is also contributing increased soil erosion and sediment loads. At the Imha-dam watershed, outflow has increased sharply by the typhoons Rusa and Maemi in 2002, 2003 respectively. In this study, the Soil and Water Assessment Tool (SWAT) model was evaluated for simulation of flow and sediment behaviors with long-term temporal and spatial conditions. The precipitation data from eight precipitation observatories, located at Ilwol, Subi and etc., were used. There was no significant difference in monthly rainfall for 8 locations. However, there was slight differences in rainfall amounts and patterns in 2003 and 2004. The topographical map at 1:5000 scale from the National Geographic Information Institute was used to define watershed boundaries, the detailed soil map at 1:25,000 scale from the National Institute of Highland Agriculture and the land cover data from the Korea Institute of Water and Environment were used to simulate the hydrologic response and soil erosion and sediment behaviors. To evaluate hydrologic component of the SWAT model, calibration was performed for the period from Jan. 2002 to Dec. 2003, and validation for Jan. 2004 to Apr. 2005. The $R^2$ value and El value were 0.93 and 0.90 respectively for calibration period, and the $R^2$ value and El value for validation were 0.73 and 0.68 respectively. The $R^2$ value and El value of sediment yield data with the calibrated parameters was 0.89 and 0.84 respectively. The comparisons with the measured data showed that the SWAT model is applicable to simulate hydrology and sediment behaviors at Imha dam watershed. With proper representation of the Best Management Practices (BM Ps) in the SWAT model, the SWAT can be used for pre-evaluation of the cost-effective and sustainable soil erosion BMPs to solve sediment issues at the Imha-dam watershed. In Korea, the Universal Soil Loss Equation (USLE) has been used to estimate the soil loss for over 30 years. However, there are limitations in the field scale mdel, USLE when applied for watershed. Also, the soil loss changes temporarily and spatially, for example, the Imha-dam watershed. Thus, the SW AT model, capable of simulating hydrologic and soil erosion/sediment behaviors temporarily and spatially at watershed scale, should be used to solve the muddy water issues at the Imha-dam watershed to establish more effective muddy water reduction countermeasure.
Jeong, Eun-Jeong;Choi, Yoo-Jeong;Lee, Gunyoung;Yun, Sang Soon;Lim, Ho Soo;Kim, MeeKyung;Kim, Yong-Suk
Journal of Food Hygiene and Safety
/
v.33
no.6
/
pp.466-473
/
2018
An analytical method of sodium polyacrylate in processed food products was developed and monitored by using size-exclusion chromatography. GF-7M HQ column and UV/VIS detector were selected based on peak shape and linearity. Flow rate, column oven temperature, and mobile phase were selected as 0.6 mL/min, $45^{\circ}C$, and 50 mM sodium phosphate buffer of pH 9.0, respectively. Samples for analysis of sodium polyacrylate were extracted with 50 mM sodium phosphate buffer of pH 7.0 for 3 hr at $20^{\circ}C$ and 150 rpm. Analytical method validation revealed proper selectivity and calibration curve was selected in the range of 50-500 mg/L, and correlation coefficient of calibration curve was more than 0.9985. Limit of detection of sodium polyacrylate was 10.95 mg/kg and limit of quantification was 33.19 mg/kg. Accuracy and coefficient of variation for sodium polyacrylate analysis was 99.6-127.6%, 3.0-8.3% for intra-day and 94.3-121.9%, 1.3-2.6% for inter-day, respectively. Sodium polyacrylate was detected in 40 samples among monitored 125 processed food products. Detected contents were less than 0.2%, limited by the Food Additives Code. Results suggest the established size-exclusion chromatography method could be used to analyze sodium polyacrylate in processed food products.
Kim, Ji Hea;Lee, Ki Won;Oh, Mirae;Choi, Ki Choon;Yang, Seung Hak;Kim, Won Ho;Park, Hyung Soo
Journal of The Korean Society of Grassland and Forage Science
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v.39
no.2
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pp.114-120
/
2019
This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.
An analytical method was developed for the determination of sedaxane in agricultural products using liquid chromatograph-tandem mass spectrometry (LC-MS/MS). The samples were extracted with acetonitrile and partitioned with dichloromethane to remove the interference, and then purified by using silica SPE cartridges to clean up. The analytes were quantified and confirmed by using LC-MS/MS in positive ion mode using multiple reaction monitoring (MRM). The matrix-matched calibration curves were linear over the calibration ranges ($0.001-0.25{\mu}g/mL$) into a blank extract with $r^2$>0.99. For validation, recovery tests were carried out at three different concentration levels (LOQ, 10LOQ, and 50LOQ, n=5) with five replicates performed at each level. The recoveries were ranged between 74.5 to 100.8% with relative standard deviations (RSDs) of less than 12.1% for all analytes. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for sedaxane determination in agricultural commodities.
Experiments for validation of surface reflectance produced by Korea Multi-Purpose Satellite (KOMPSAT-3A) were conducted using Chinese Baotou (BTCN) data among four sites of the Radical Calibration Network (RadCalNet), a portal that provides spectrophotometric reflectance measurements. The atmosphere reflectance and surface reflectance products were generated using an extension program of an open-source Orfeo ToolBox (OTB), which was redesigned and implemented to extract those reflectance products in batches. Three image data sets of 2016, 2017, and 2018 were taken into account of the two sensor model variability, ver. 1.4 released in 2017 and ver. 1.5 in 2019, such as gain and offset applied to the absolute atmospheric correction. The results of applying these sensor model variables showed that the reflectance products by ver. 1.4 were relatively well-matched with RadCalNet BTCN data, compared to ones by ver. 1.5. On the other hand, the reflectance products obtained from the Landsat-8 by the USGS LaSRC algorithm and Sentinel-2B images using the SNAP Sen2Cor program were used to quantitatively verify the differences in those of KOMPSAT-3A. Based on the RadCalNet BTCN data, the differences between the surface reflectance of KOMPSAT-3A image were shown to be highly consistent with B band as -0.031 to 0.034, G band as -0.001 to 0.055, R band as -0.072 to 0.037, and NIR band as -0.060 to 0.022. The surface reflectance of KOMPSAT-3A also indicated the accuracy level for further applications, compared to those of Landsat-8 and Sentinel-2B images. The results of this study are meaningful in confirming the applicability of Analysis Ready Data (ARD) to the surface reflectance on high-resolution satellites.
Park, Geun-Ae;Ahn, So-Ra;Park, Min-Ji;Kim, Seong-Joon
KSCE Journal of Civil and Environmental Engineering Research
/
v.30
no.2B
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pp.121-135
/
2010
This study is to assess the effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water supply using the SLURP. Before the future analysis, the SLURP model was calibrated using the 6 years daily streamflow records (1998-200398 and validated using 3 years streamflow data (2004-200698 for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang8 and Gosam98located in Anseongcheon watershed. The calibration and validation results showed that the model was able to simulate the daily streamflow well considering the reservoir operation for paddy irrigation and flood discharge, with a coefficient of determination and Nash-Sutcliffe efficiency ranging from s 7 to s 9 and 0.5 to s 8 respectively. Then, the future potential climate change impact was assessed using the future wthe fu data was downscaled by nge impFactor method throuih bias-correction, the future land uses wtre predicted by modified CA-Markov technique, and the future ve potentiacovfu information was predicted and considered by the linear regression bpowten mecthly NDVI from NOAA AVHRR ima ps and mecthly mean temperature. The future (2020s, 2050s and 2e 0s) reservoir inflow, the temporal changes of reservoir storaimpand its impact to downstream streamflow watershed wtre analyzed for the A2 and B2 climate change scenarios based on a base year (2005). At an annual temporal scale, the reservoir inflow and storaimpchange oue, anagricultural reservoir wtre projected to big decrease innautumnnunder all possiblmpcombinations of conditions. The future streamflow, soossmoosture and grounwater recharge decreased slightly, whtre as the evapotransporation was projected to increase largely for all possiblmpcombinations of the conditions. At last, this study was analysed contribution of weather, vegetation and land use change to assess which factor biggest impact on agricultural reservoir and stream watershed. As a result, weather change biggest impact on agricultural reservoir inflow, storage, streamflow, evapotranspiration, soil moisture and groundwater recharge.
An isocratic high performance liquid chromatography (HPLC) method for routine analysis of deoxynivalenol in noodles was validated and estimated the measurement uncertainty. Noodles (dried noodle and ramyeon) were analyzed by HPLC-ultraviolet detection using immunoaffinity column for clean-up. The limits of detection (LOD) and quantification (LOQ) were 7.5 ${\mu}g$/kg and 18.8 ${\mu}g$/kg, respectively. The calibration curve showed a good linearity, with correlation coefficients $r^2$ of 0.9999 in the concentration range from 20 to 500 ${\mu}g$/kg. Recoveries and Repeatabilities expressed as coefficients of variation (CV) spiked with 200 and 500 ${\mu}g$/kg were $82{\pm}2.7%$ and $87{\pm}1.3%$% in dried noodle, and $97{\pm}1.6%$ and $91{\pm}12.0%$ in ramyeon, respectively. The uncertainty sources in measurement process were identified as sample weight, final volume, and sample concentration in extraction volume as well as components such as standard stock solution, working standard solution, 5 standard solutions, calibration curve, matrix, and instrument. Deoxynivalenol concentration and expanded uncertainty in two matrixes spiked with 200 ${\mu}g$/kg and 500 ${\mu}g$/kg were estimated to be $163.8{\pm}52.1$ and $435.2{\pm}91.6\;{\mu}g$/kg for dried noodle, and $194.3{\pm}33.0$ and $453.2{\pm}91.1\;{\mu}g$/kg for ramyeon using a coverage factor of two which gives a level of statistical confidence with approximately 95%. The most influential component among uncertainty sources was the recovery of matrix, followed by calibration curve.
Journal of the Korean Data and Information Science Society
/
v.24
no.6
/
pp.1319-1329
/
2013
The purpose of this research was to develop and validate the coach-athlete relationship scale suitable to amateur golf players by applying the Rasch rating scale model. As the coach-athlete relationship scale, the Korean form of scale developed by Kim and Park (2008), which was revised based on the evidence on the basis of inspection contents, was used to conduct a survey on 217 amateur golf athletes. And the unidimensionality, which is the basic assumption of the Rasch model, was verified using the WINSTEPS program, and the appropriateness of the item category was established through the step calibration. The goodness of fit of each question was tested through the goodness-of-fit index and the differential item functioning (DIF) was estimated according to the golf career. When the goodness-of-fit index estimated for each question was 1.30 or more it was judged unfit and the significance level in the analysis was all set as.05. The results of the analysis showed that the measures variance explained by the Rasch measurement model was more (33.7%) than 20%, so the unidimensionality assumptions of the 11 questions (..hospitable posture when my coach is teaching) were satisfied. The result of analyzing the item category (7 scale) with step calibration was found to be unfit, but in the result of reanalyzing by rescoring into a 5-point scale, it was found to be fit. Particularly, in the result of estimating the goodness-of-fit using the systematized item category (5 scale), Question 10 (...my best when my coach is teaching) and Question 11 were found to be unfit, and as a result of estimating the differential functioning item according to golf career, Question 11 was found to be unevenly differentiated according to golf career. So the 5-point scale of Question 9 after eliminating the two questions which were unfit and differentiated was validated to be the coach-athlete relationship scale suitable to amateur golf athletes.
A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R2, and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.
Kim, Young-Hyun;Bae, Da-Bin;Park, Sun-Ok;Lee, Sang-Jong;Cho, Ok-Hyun;Lee, Ok-Hwan
Journal of the Korean Society of Food Science and Nutrition
/
v.42
no.9
/
pp.1419-1425
/
2013
The aim of this study was to investigate the method validation for the determination of eleutherosides (B and E) and ${\beta}$-glucan in Acanthopanax (A.) koreanum. This medicinal plant reportedly mainly included eleutherosides which exhibit the pharmacological effects, and ${\beta}$-glucan substantially enhances the function of the immune system by activating macrophages. The specificity, linearity, precision, accuracy, limit of detection (LOD, S/N=3), and limit of quantification (LOQ, S/N=10) were measured by HPLC and enzymatic methods. Our results showed that the coefficient of calibration correlation ($R^2$) for eleutheroside B and E were 0.9997 and 0.9999, respectively. The limits of detection (LOD) for eleutheroside B and E were $0.050{\mu}g/mL$ and $0.025{\mu}g/mL$, respectively. The recovery rate of eleutheroside B and E were revealed in the high range of 100.66~110.04% and 94.26~111.62%, respectively. The inter-day precision of eleutheroside B and E in the root and stem in A. koreanum were 1.4~5.0% and 1.1~2.5%, respectively. The intra-day precision of eleutheroside B and E in the root and stem in A. koreanum were 2.8~2.9% and 0.4~1.1%, respectively. Furthermore, the inter-day and intra-day precision of ${\beta}$-glucan in the stem, leaf, and fruit of A. koreanum were 1.32~5.67% and 8.01~11.76%, respectively. In conclusion, the methods were validated for the detection of eleutherosides and ${\beta}$-glucan in A. koreanum.
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