• Journal of Food Hygiene and Safety
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• v.31 no.5
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• pp.319-326
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• 2016

Colistin is a last resort antimicrobial agent against multi-drug resistant Gram-negative bacteria. This study was conducted to develop an analytical method to determine colistin in fish and shrimp. The analytes were confirmed and quantified via liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the positive ion mode using multiple reaction monitoring (MRM). The sample was extracted with acidified 5% methanol (containing 0.5% formic acid). Then, solid phase extraction (SPE) was used for cleanup. Matrix-matched calibration curves were linear over the calibration ranges (0.05-1.2 mg/kg) for all the analytes into blank sample with $r^2$ > 0.99. All the values fulfilled the criteria requested by the Codex guidelines. Average recoveries ranged from 85.9% to 107.9%. The repeatability of measurements, expressed as the coefficient of variation (CV, %), was less than 15%. The limit of detection (LOD) was 0.02 mg/kg, and the limit of quantitation (LOQ) was 0.05 mg/kg. This improved method showed higher accuracy and acceptable sensitivity to meet the CAC guideline requirements and is applicable for the analysis of residual colistin (A+B) in fish and shrimp.

• Korean Journal of Food Science and Technology
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• v.45 no.6
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• pp.693-699
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• 2013

A simple, sensitive, and specific method for quantifying the nicotine content of synthetic favoring substances (SFS) was developed using high performance liquid chromatography (HPLC) with a photo-diode array detector (PDA). Nicotine was extracted from SFS samples by using an acid-base liquid-liquid extraction method with dichloromethane and distilled water. The nicotine content was quantified by HPLC/PDA (261.9 nm) with a $C_{18}$ column under a gradient of 10% acetonitrile with 20 mM ammonium formate (ammonia solution adjusted to pH 8.7) to 100% acetonitrile. The calibration curve, analyzed from concentration standards between 0.1 to 2 mg/L, presented linearity with a correlation coefficient ($r^2$)>0.9999. The limit of quantitation (LOQ) of nicotine in SFS was 0.4 mg/kg, and the average recoveries ranged from 76.4% to 96.3%. The repeatability of measurements, expressed as the coefficient of variation (CV%), ranged from 1.74 to 5.12%. This newly developed method for nicotine quantification in SFS can be considered an analytical method with an acceptable level of sensitivity and repeatability.

• Korean Journal of Food Science and Technology
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• v.38 no.1
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• pp.1-4
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• 2006

Method of analyzing sodium alginate in foods was developed using high performance liquid chromatography (HPLC). HPLC conditions for sodium alginate were: column, MCI GEL $(8\;mm\;i.d{\times}300\;mm)$; mobile phase, deionized water; detector, refractive index detection (sensitivity = 16). Separation of sodium alginate was achieved within 15 min. Sodium alginate showed good linear relationship at 0.1-2.0% range. Correlation coefficient of calibration curve for sodium alginate exceeded 0.999, and detection limit was 0.005%. Recovery rate of sodium alginate in wheat flour dough was 106.67%. This method was successfully applied to analyses of cereals, saccharides, and ice cream, etc. Sodium alginate was detected in chocolate, noodles, and kelp at 0-44.8% range.

• Korean Journal of Environmental Agriculture
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• v.32 no.1
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• pp.70-77
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• 2013

BACKGROUND: Nitroxoline is an antibiotic agent. It is used for the treatment of the second bacterial infection by the colibacillosis, salmonellosis and viral disease of the poultry. When the nitroxoline is indiscreetly used, the problem about the abuse of the antibiotics can occur. Therefore, this study presented the residue analytical method of nitroxoline in food for the safety management of animal farming products. METHODS AND RESULTS: A simple, sensitive and specific method for nitroxoline in chicken muscle by high performance liquid chromatograph with PDA was developed. Sample extraction with acetonitrile, purification with SPE cartridge (MCX) were applied, then quantitation by HPLC with C18 column under the gradient condition with 0.1 % tetrabutylammonium hydroxide-phosphoric acid and methanol was performed. Standard calibration curve presented linearity with the correlation coefficient ($r^2$) > 0.999, analysed from 0.02 to 0.5 mg/L concentration. Limit of quantitation in chicken muscle showed 0.02 mg/kg, and average recoveries ranged from 72.9 to 88.1 % in chicken muscle. The repeatability of measurements expressed as coefficient of variation (CV %) was less than 12 % in 0.02 and 0.04 mg/kg. CONCLUSION(S): Newly developed method for nitroxoline in chicken muscle was applicable to food inspection with the acceptable level of sensitivity, repeatability and reproducibility.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.10
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• pp.39-50
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• 1998

Wide-band sharp-transition filters are widely used in applications such as wireless CODEC design or medical systems. Since these filters suffer from large sensitivity and roundoff noise, large word-length is required for the VLSI implementation, which increases the hardware size and the power consumption of the chip. In this paper, a low-power implementation technique for digital filters with wide-band sharp-transition characteristics is proposed using CPL (Complementary Pass-Transistor Logic), LWDF (Lattice Wave Digital Filter) and a modified DIFIR (Decomposed & Interpolated FIR) algorithm. To reduce the short-circuit current component in CPL circuits due to threshold voltage reduction through the pass transistor, three different approaches can be used: cross-coupled PMOS latch, PMOS body biasing and weak PMOS latch. Of the three, the cross-coupled PMOS latch approach is the most realistic solution when the noise margin as well as the energy-delay product is considered. To optimize CPL transistor size with insight, the empirical formulas for the delay and energy consumption in the basic structure of CPL circuits were derived from the simulation results. In addition, the filter coefficients are encoded using CSD (Canonic Signed Digit) format and optimized by a coefficient quantization program. The hardware cost is minimized further by a modified DIFIR algorithm. Simulation result shows that the proposed method can achieve about 38% reductions in power consumption compared with the conventional method.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.867-880
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• 2006

Hydrological models with many parameters and complex model structures require a powerful and detailed model calibration/validation scheme. In this study, we proposed a multi-variable and multi-site calibration and validation framework for the Soil Water Assessment Tool (SWAT) model applied in the Gap-cheon catchment located downstream of the Geum river basin. The sensitivity analysis conducted before main calibration helped understand various hydrological processes and the characteristics of subcatchments by identifying sensitive parameters in the model. In addition, the model's parameters were estimated based on existing data prior to calibration in order to increase the validity of model. The Nash-Sutcliffe coefficients and correlation coefficient were used to estimate compare model output with the observed streamflow data: $R_{eff}\;and\;R^2$ ranged 0.41-0.84 and 0.5-0.86, respectively, at the Heuduck station. Model reproduced baseflow estimated using recursive digital filter except for 2-5% overestimation at the Sindae and Boksu stations. Model also reproduced the temporal variability and fluctuation magnitude of observed groundwater levels with $R^2$ of 0.71 except for certain periods. Therefore, it was concluded that the use of multi-variable and multi-site method provided high confidence for the structure and estimated parameter values of the model.

• Analytical Science and Technology
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• v.31 no.1
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• pp.23-30
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• 2018

Twenty-two allergy-induced aromatics in children were analyzed using a gas chromatography flame ionization detector (GC-FID) and gas chromatography mass spectrometer (GC-MSD). Analytes were extracted using an automatic Soxhlet extractor and centrifuged for 10 min in a fast freezing centrifuge, and the supernatant was transferred into a 2 mL vial and injected in split mode. Under the established conditions, the calibration curve showed linearity with a correlation coefficient of 0.996 or more. A wide range of sensitivity of 6.7 to 1,859,839 depending on the device characteristics and detector used was shown. The detection limit of the device was 0.0032 to $0.0335{\mu}g/mL$, and the maximum detection limit was less than $0.1{\mu}g/mL$. The detection limit of the method ranged from 0.0033 to $0.1161{\mu}g/mL$. In addition, the limit of quantification ranged from 0.0100 to $0.5422{\mu}g/mL$, with a level of precision ranging from 0.21 % to 4.89 % and a degree of accuracy ranging from 89 % to 111 %. The analytical method developed in this study was applied to commercial products.

• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.1-8
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• 2000

One of today's very critical and sensitive accurate accelerometer which can be used higher temperature than $200^{\circ}C$ and corrosive environment, is particularly demanded for automotive engine. Because silicon is a material of large temperature dependent coefficient, and the piezoresistors are isolated with p-n junctions, and its leakage current increase with temperature, the performance of the silicon accelerometer degrades especially after $150^{\circ}C$. In this paper, The temperature characteristic of a accelerometer using silicon on insulator (SOI) structure is studied theoretically, and compared with experimental results. The temperature coefficients of sensitivity and offset voltage (TCS and TCO) are related to some factors such as thermal residual stress, and are expressed numerically. Thermal stress analysis of the accelerometer has also been carried out with the finite-element method(FEM) simulation program ANSYS. TCS of this accelerometer can be reduced to control the impurity concentration of piezoresistors, and TCO is related to factors such as process variation and thermal residual stress on the piezoresistors. In real packaging, The avarage thermal residual stress in the center support structure was estimated at around $3.7{\times}10^4Nm^{-2}^{\circ}C^{-1}$ at sensing resistor. The simulated ${\gamma}_{pT}$ of the center support structure was smaller than one-tenth as compared with that of the surrounding support structure.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.217-217
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• 2015

The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.299-310
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• 2021

Glycerol is a non-volatile compound with no aromatic properties that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is also the third most significant byproduct of alcoholic fermentation in terms of quantity after ethanol and carbon dioxide. In this study, Fourier transform infrared (FT-IR) spectroscopy was employed as a fast non-destructive method in conjugation with multivariate regression analysis to build a model for the quantitative analysis of glycerol concentration in wine samples. The samples were prepared by using three varieties of red wine samples (i.e., Shiraz, Merlot, and Barbaresco) that were adulterated with glycerol in concentration ranges from 0.1 to 15% (v·v^-1), and subjected to analysis together with pure wine samples. A net analyte signal (NAS)-based methodology, called hybrid linear analysis in the literature (HLA/GO), was applied for predicting glycerol concentrations in the collected FT-IR spectral data. Calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results exhibited a high coefficient of determination (R²) of 0.987 and a low root mean square error (RMSE) of 0.563% for the calibration set, and a R² of 0.984 and a RMSE of 0.626% for the validation set. Further, the model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, and the results confirmed that this model can be used in most applications, as well as for quality assurance.