• Analytical Science and Technology
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• v.24 no.4
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• pp.243-248
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• 2011

A selective determination method of mercury (II) ion in aqueous solution by luminol-based chemiluminescence system (luminol CL system) has been developed. Determination of metal ions such as copper (II), iron (III), chromium (III) ion in solution by the luminol CL system using its catalytic role in the reaction of luminol and hydrogen peroxide has been reported by several groups. In this study, the catalytic activity of mercury (II) ion in the reaction of luminol and hydrogen peroxide was observed by the enhanced CL intensity of the luminol CL system. Based on this phenomenon, experimental conditions of the luminol CL system were investigated and optimized to determine mercury (II) ion in aqueous solution. While mercury (II) ion in mixed sample solution containing mercury (I) and (II) ions highly enhanced the CL intensity of the luminol CL system, the mercury (I) ion could not enhanced the CL intensity. Thus selective determination of the mercury (II) ions in a mixture containing mercury (I) and (II) ions could be achieved. Each concentration of mercury (I) and (II) ions in aqueous solution can be obtained from the results of the CL method that give the concentration of only mercury (II) ion and the inductively coupled plasma (ICP) method that give the total concentration of mercury ions. On the optimized conditions, the calibration curve of mercury (II) ion was linear over the range from $1.25{\times}10^{-5}$ to $2.50{\times}10^{-3}M$ with correlation coefficient of 0.991. The detection limit of mercury (II) ion in aqueous solution was calculated to be $1.25{\times}10^{-7}M$.

• Analytical Science and Technology
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• v.25 no.3
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• pp.171-177
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• 2012

A determination method of aromatic amino acids such as trytophan (Trp), tyrosine (Tyr), and phenylalanine (Phe) using luminol-$H_2O_2$-Cu(II) system has been presented. In the presence of an aromatic amino acid, the enhanced chemiluminescence (CL) intensity of luminol-$H_2O_2$-Cu(II) system was obtained by forming a complex between Cu(II) and the amino acid. Based on the above phenomenon, a sensitive and fast determination of three aromatic amino acids was performed using the CL method in batch-type detection system. To optimize determination conditions, the kinetic influence of an aromatic amino acid on the luminol-$H_2O_2$-Cu(II) system and the effects of $H_2O_2$ and Cu(II) concentration, pH, and buffers were investigated. Under the optimized conditions, the calibration curve was linear over the range from $1.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Trp, $1.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Try, and $2.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Phe, respectively. In this range, reproducibility (RSD, n = 4) of Trp, Try, and Phe were 3.21%, 2.64%, and 2.48%, respectively. The limit of detection ($3{\sigma}/s$) was calculated to be $6.8{\times}10^{-7}\;M$ for Trp, $5.7{\times}10^{-7}\;M$ for Try, and $9.6{\times}10^{-7}\;M$ for Phe.

• 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 Soil Science and Fertilizer
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• v.42 no.5
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• pp.399-407
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• 2009

Laser induced breakdown spectroscopy(LIBS) is an simple analysis method for directly quantifying many kinds of soil micro-elements on site using a small size of laser without pre-treatment at any property of materials(solid, liquid and gas). The purpose of this study were to find an optimum condition of the LIBS measurement including wavelengths for quantifying soil elements, to relate spectral properties to the concentration of soil elements using LIBS as a simultaneous un-breakdown quantitative analysis technology, which can be applied for the safety assessment of agricultural products and precision agriculture, and to compare the results with a standardized chemical analysis method. Soil samples classified as fine-silty, mixed, thermic Typic Hapludalf(Memphis series) from grassland and uplands in Tennessee, USA were collected, crushed, and prepared for further analysis or LIBS measurement. The samples were measured using LIBS ranged from 200 to 600 nm(0.03 nm interval) with a Nd:YAG laser at 532 nm, with a beam energy of 25 mJ per pulse, a pulse width of 5 ns, and a repetition rate of 10 Hz. The optimum wavelength(${\lambda}nm$) of LIBS for estimating soil and plant elements were 308.2 nm for Al, 428.3 nm for Ca, 247.8 nm for T-C, 438.3 nm for Fe, 766.5 nm for K, 85.2 nm for Mg, 330.2 nm for Na, 213.6 nm for P, 180.7 nm for S, 288.2 nm for Si, and 351.9 nm for Ti, respectively. Coefficients of determination($r^2$) of calibration curve using standard reference soil samples for each element from LIBS measurement were ranged from 0.863 to 0.977. In comparison with ICP-AES(Inductively coupled plasma atomic emission spectroscopy) measurement, measurement error in terms of relative standard error were calculated. Silicon dioxide(SiO2) concentration estimated from two methods showed good agreement with -3.5% of relative standard error. The relative standard errors for the other elements were high. It implies that the prediction accuracy is low which might be caused by matrix effect such as particle size and constituent of soils. It is necessary to enhance the measurement and prediction accuracy of LIBS by improving pretreatment process, standard reference soil samples, and measurement method for a reliable quantification method.