• Mass Spectrometry Letters
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• v.5 no.2
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• pp.42-48
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• 2014

A specific and sensitive liquid chromatography-electrospray ionization tandem mass spectrometry method (LC-ESI-MS/MS) was developed and validated for the simultaneous quantification of porphyrins (coproporphyrin, pentacarboxylporphyrin, hexacarboxylporphyrin, heptacarboxylporphyrin, and uroporphyrin) in human plasma and urine. Acidified plasma samples and urine samples were prepared by using liquid-liquid extraction using ethyl acetate and protein precipitation with acetonitrile, respectively. The separation was achieved onto a Synergi Fusion RP column ($150mm{\times}2.0mm$, $4{\mu}m$) with a gradient elution of mobile phase A (0.1% formic acid in 2 mmol/L ammonium acetate, v/v) and mobile phase B (20% methanol in acetonitrile, v/v) at a flow rate of $450{\mu}L$/min. Porphyrins and the internal standard (IS), coproporphyrin I-$^{15}N_4$, were detected by a tandem mass spectrometer equipped with an electrospray ion source operating in positive ion mode. Multiple reaction monitoring (MRM) transitions of the protonated precursor ions and the related product ions were optimized to increase selectivity and sensitivity. The proposed method was validated by assessing selectivity, linearity, limit of quantification (LOQ), precision, accuracy, recovery, and stability. The calibration curves were obtained in the range of 0.1-100 nmol/L and the LOQs were estimated as 0.1 nmol/L for all porphyrins. Results obtained from the validation study of porphyrins showed good accuracy, precision, recovery, and stability. Finally, the proposed method was successfully applied to clinical studies on the autism spectrum disorder (ASD) diagnosis of 203 Korean children.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.2
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• pp.125-130
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• 2015

The objective of this study was to investigate the feasibility of using near infrared spectroscopy (NIRS) to discriminate between grass spices. A combination of NIRS and chemometrics was used to discriminate between Italian ryegrass, perennial ryegrass, and tall fescue seeds. A total of 240 samples were used to develop the best discriminant equation, whereby three spectra range (visible, NIR, and full range) were applied within a 680 nm to 2500 nm wavelength. The calibration equation for the discriminant analysis was developed using partial least square (PLS) regression and discrimination equation (DE) analysis. A PLS discriminant analysis model for the three spectra range that was developed with the mathematic pretreatment "1,8,8,1" successfully discriminated between Italian ryegrass, perennial ryegrass, and tall fescue. An external validation indicated that all of the samples were discriminated correctly. The discriminant accuracy was shown as 68%, 78%, and 73% for Italian ryegrass, perennial ryegrass, and tall fescue, respectively, with the NIR full-range spectra. The results demonstrate the usefulness of the NIRS-chemometrics combination as a rapid method for the discrimination of grass species by seed.

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1095-1106
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• 2008

Climate change and global warming are prevalent all over the world in this century and many researchers including hydrologists have studied on the climate change. This study also studied the impact of climate change on streamflows of a basin in Korea. The SWAT model was used to assess the impacts of potential future climate change on the streamflows of the Daecheong Dam Basin. Calibration and validation of SWAT were performed on a monthly basis for the year of 1982-1995 and 1996-2005, respectively. The impact of seven 15-year(1988-2002) scenarios were then analyzed for comparing it to the baseline scenario. Among them, scenario 1 was set to show the result of doubling $CO_2$, scenario 2-6 were set to show the results of temperature and precipitation change, and scenario 7 was set to show the result of the combination of climatologic components. A doubling of atmospheric $CO_2$ concentration is predicted to result in an maximum monthly flow increase of 11 percent. Non-linear impacts were predicted among precipitation change scenarios of -42, -17, 17, and 42 percent, which resulted in average annual flow changes in Daecheong Dam Basin of -55, -24, 25, and 64 percent. The changes in streamflow indicate that the Daecheong Dam Basin is very sensitive to potential future climate changes and that these changes could stimulate the increased period or severity of flood or drought events.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.296-313
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• 2014

A QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) multiresidue method was developed for the simultaneous analysis of 124 pesticides in soil by LC-MS. The procedure involved liquid extraction of soil immersed with 0.2N $NH_4Cl$ by acetonitrile with 1% acetic acid, followed by anhydrous $MgSO_4$ and sodium acetate, and dispersive SPE cleanup with $MgSO_4$, primary secondary amine (PSA) and $C_{18}$. The extracts were analyzed with LC-MS/MS in ESI positive mode. Standard calibration curves were made by matrix matched standards and their correlation coefficients were higher than 0.99. Recovery studies for the validation were carried out using two type soils, loam and sandy loam, at four concentration levels (0.005, 0.01, 0.02, and 0.1 mg/kg). The recoveries of pesticides were in the range of 70-120% with < 20% RSD except 4 pesticides, Benfuracarb, Ethiofencarb, Pymetrozine, and Pyrethrin. This result indicated that the method using QuEChERS and LC-MS/MS could be applied for the simultaneous determination of pesticide residues in soils.

• Journal of Food Hygiene and Safety
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• v.22 no.4
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• pp.257-267
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• 2007

The possibility of rapid non-destructive qualitative and quantitative analysis of vegetable oils such as perilla, com, soybean and rapaseed oils in sesame oils was evaluated. A calibration equation calculated by MPLS(Modified Partial Least Squares) regression technique was developed and coefficients of determination for perilla oil, com oil, soybean oil and rapaseed oil contents were 0.9992, 0.9694, 0.9795 and 0.9790 respectively. According to the data obtained from validation study, $R^2$ of contents of perilla, com, soybean, rapaseed oils were 0.997, 0.848, 0.957 and 0.968, and SEP of content of them 0.747, 5.069, 3.063 and 3.000 by MPLS respectively. The results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the rapid and simple measurement of sesame oil mixed with other vegetable oils. The detection limits of the NIRS for perilla oil, com oil, soybean oil and rapaseed oil were presumed as 2%, $15{\sim}20%,\;15{\sim}20%$ and 10%, respectively.

• Journal of Food Hygiene and Safety
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• v.32 no.3
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• pp.193-198
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• 2017

Scutellaria baicalensis, Eleutherococcus senticosus, and Angelica sinensis have been used as raw materials for health functional foods. This study was conducted to develop a novel method to analyze levels of baicalin (Scutellaria baicalensis), eleutheroside E (Eleutherococcus senticosus), and ligustilide (Angelica sinensis) simultaneously in health functional foods. The methanol extracted samples were analyzed and quantified via liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the positive ion mode and the negative ion mode using multiple reaction monitoring. Standard calibration curves confirmed linearity with the correlation coefficient ($r^2$) of > 0.99 at $100-2000{\mu}g/mL$ concentration range. The limits of detection (LODs) and limits of quantitation (LOQs) were in the range of $13.0{\sim}35.2{\mu}g/L$ and $39.3{\sim}106.7{\mu}g/L$, respectively. The recovery results ranged between 91.4~109.9% at 3 different concentration levels with relative standard deviations (RSDs) less than 5%. The proposed analytical method was characterized with high accuracy and acceptable precision. The new method would be an effective tool to analyze baicalin, eleutheroside E, and ligustilide simultaneously in raw materials of health functional foods.

• Journal of Ginseng Research
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• v.33 no.1
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• pp.8-12
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• 2009

A simple gradient HPLC method for rapid determination of major ginsenosides ($Rg_1$ and $Rb_1$) and unique ginsenoside (Rf) of Korean ginseng (Panax ginseng C.A. Meyer) was developed. Within 50min, three ginsenosides have been separated and identified on $\mu$-Bondapak $C_{18}$ column ($3.9{\times}300\;mm$, $10{\mu}m$) with gradient elution using water and acetonitrile as a mobile phase. The method was validated in terms of linearity, accuracy, and precision. The correlation coefficients ($r^2$) for calibration curves of ginsenosides were over 0.9997. The developed HPLC method was successfully applied to the analysis of ginseng samples and the recoveries of ginsenosides were in the range of $101.1{\sim}115%$ with RSD<3.2%. The developed method could be used for rapid evaluation of the ginsenosides $Rg_1$, $Rb_1$, and Rf.

• Journal of Ginseng Research
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• v.37 no.1
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• pp.135-141
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• 2013

A rapid, sensitive and selective analytical method was developed and validated for the determination of compound K, a major intestinal bacterial metabolite of ginsenosides in human plasma. Liquid-liquid extraction was used for sample preparation and analysis, followed by liquid chromatography tandem spectrometric analysis and an electrospray-ionization interface. Compound K was analyzed on a Phenomenex Luna C18 column ($100{\times}2.00$ mm, 3 ${\mu}m$) with the mobile phase run isocratically with 10 mM ammonium acetate-methanol-acetonitrile (5:47.5:47.5, v/v/v) at a flow rate of 0.5 mL/min. The method was validated for accuracy (relative error <12.63%), precision (coefficient of variation <9.14%), linearity, and recovery. The assay was linear over the entire range of calibration standards i.e., a concentration range of 1 ng/mL to 1,000 ng/mL ($r^2$ >0.9968). The recoveries of compound K after liquid-liquid extraction at 1, 2, 400, and 800 ng/mL were $106.00{\pm}0.08%$, $103.50{\pm}0.19%$, $111.45{\pm}5.21%$, and $89.62{\pm}34.46%$ for intra-day and $85.40{\pm}0.08%$, $94.50{\pm}0.09%$, $112.50{\pm}5.21%$, and $95.87{\pm}34.46%$ for inter-day, respectively. The lower limit of quantification of the analytical method of compound K was 1 ng/mL in human plasma. The developed method was successfully applied to a pharmacokinetic study of compound K after oral administration in ten of healthy human subjects.

• Food Science and Preservation
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• v.22 no.4
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• pp.559-566
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• 2015

The aim of this study was to develop an analytical method for determination of T-2 toxin and HT-2 toxin level in cereals and to survey their levels using LC-MS/MS. The T-2 and HT-2 toxins were simultaneously analyzed by electrospray ionization with a positive ion mode and multiple reaction monitoring (MRM) after filteration and immuno-affinity column clean-up. A matrix-matched standard calibration used for quantification and recoveries of T-2 and HT-3 toxins were in the range of $100.6{\pm}7.2%$ and $96.8{\pm}9.4%$, respectively. Limits of detection and quantification of T-2 and HT-2 toxins were estimated to be 0.5 and $1.5{\mu}g/kg$, respectively. Each repeatability (RSRr) of T-2 and HT-2 toxins was determined to be 0.9~6.0%, and 4.9~6.1%, respectively. Total 115 samples cereals were collected from 9 types of cereals for analysis. The positive percentages of T-2 and HT-2 toxins obtained from collected samples were found to be 72% and 80%, respectively. The contamination level of T-2 toxin and HT-2 toxin in cereals were $37.1{\mu}g/kg$, and $5.4{\mu}g/kg$, respectively. Therefore, this study suggests that the developed method could be an useful analytical method to determine the T-2 and HT-2 toxin level in cereals and the present data could be used as a reference to estimate the risk assessment.