• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1192-1192
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• 2001

Usually there are many furnaces in a ethylene plant and the performance of total furnaces can be improved if that of each furnace is monitored and controlled. For this purpose real-time data for the effluent of each furnace is necessary. However, it is very difficult to analyze the total effluent stream of a ethylene furnace by real-time because it is composed of so many components including heavy hydrocarbons. Fortunately, component data for lighter hydrocarbons is much more important than that of heavier ones for ethylene furnace. In ordinary case, the on-line measurement of light hydrocarbons is performed by on-stream gas chromatography, after separating gas-phase part from effluent. The main and important components of gas-phase are Methane, Ethane, Ethylene, and Propylene. If we can use Near-infrared spectroscopy for measuring those components within good reproducibility, shorter analysis time, better repeatability, easier maintenance and lower cost will make Near-infrared (NIR) analyzer replace on-stream gas chromatography in this process. Although it is known to be very difficult to measure gas components because of very weak absorption in Near-infrared region, we have studied the feasibility of the application of NIR for the measurement of gas-phase hydrocarbon in the effluent of ethylene furnace. The samples were obtained from actual process and NIR spectra were collected over 1100 to 2500nm range. NIR spectra and calibrations showed and demonstrated the possibility of extending NIR spectroscopy to the measurement of gas-phase hydrocarbon in the effluent of ethylene furnace.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1254-1254
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• 2001

Near infrared spectroscopy (NIRS) was applied to determination of the lipid content of compost during compost fermentation of tofu(soybean-curd) refuse. The reflected rays in the wavelength range between 800 and 2500 nm were measured at 2 nm intervals. The absorption of lipid observed at 4 wavelengths, 1208, 1712, 2312 and 2352 nm on the second derivative spectra. To formulate a calibration equation, a multiple linear regression analysis was carried out between the near-infrared spectral data and on the lipid content in the calibration sample set (sample number, n=60) obtained using a Soxhlet extraction method. The calibration equation for prediction of lipid, the value of the multiple correlation coefficient (R) was 0.975 when using the wavelengths of 1208 and 1712nm. To validate the calibration equation obtained, the lipid content in the validation sample set (n=35) not used for formulating the calibration equation were calculated using the calibration equations, and compared with the values obtained using the Soxhlet extraction method. Good agreement were observed between the results of the Soxhlet extraction method and those values of the NIRS method. The simple correlation coefficient (r) and standard error of prediction (SEP) were 0.964 and 0.815 %, respectively. Then, the NIRS method was applied to a compost fermentation in which the time course the lipid content were measured and good results were obtained. The study indicates that NIRS is a useful method for process management of the compost fermentation of tofu refuse.

• Near Infrared Analysis
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• v.1 no.2
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• pp.45-48
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• 2000

The effective component Ginsenoside in Ginseng has been widely used to cure some hypochondriasis and be as supplementary medicines. There are many chemical analysis methods to measure the contents of Ginsenoside in Ginseng; however, all these methods have some shortcomings such as long time, environmental pollution and damaging the samples. In this paper, it is possible to use near infrared spectroscopy to measure the content of Ginsenoside in Ginseng without destruction. As the results, Rg1, Rb1, Re and T-Saponin of Ginsenoside can be measured with the accuracy of R(0.81) SEP (1.704 mg/g), R(0.74) SEP (1.211 mg/g), R (0.78) SEP (1.049 mg/g) and R(0.84), SEP(4.537 mg/g).

• Near Infrared Analysis
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• v.1 no.2
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• pp.35-39
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• 2000

The purpose of this research was to find out suitable soil sample preparation and sample holding tools for NIR reflection radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1,100 to 2,500nm with an InfraAlyzer 500(Bran+Luebbe Co.). Coarse(2.0mm) and fine(0.5mm) soil sample and various sample holding tools were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter and total nitrogen of the soils. Multiple linear regression was used to obtain the best correlation of NIR spectroscopy method. Correlation of NIR spectroscopy method. Correlation of NIR spectra for finely and coarsely sized soil did not show much difference. The standard errors of prediction(SE) using different types of sample holding tools for organic matter, total nitrogen and soil moisture were better than 0.765, 0.041 and 0.63% respectively. From the results it can be concluded that NIR spectroscopy with flow type cell could be used as a fast routine testing method in quantitative determination of organic matter, total nitrogen and soil moisture.

• Journal of The Korean Society of Grassland and Forage Science
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• v.24 no.1
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• pp.81-90
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• 2004

Farmers need timely information on the nutritional status of their animals and the nutritive value of pastures and supplementary feeds if they are to apply successfully this existing nutritional information. Near infrared reflectance(NIR) spectroscopy has been used over the last forty years to analyse accurately protein, fiber, and other organic components in animal foods. NIR spectroscopy is a rapid, non-destructive, and non-polluting technology. When properly calibrated, NIR spectroscopy is used successfully with both concentrate and forage feeds. NIR methods predict in vitro digestibility accurately and precisely, and can predict in vivo digestibility at least as well as conventional "wet chemistry" methods such as in vivo digestion or the pepsin-cellulase method, and much more rapidly. NIR technology has been applied to the routine monitoring (through analysis of feces samples) of the nutritional status of cattle and other grazing animals. This report reviews the use of near infrared reflectance(NIR) spectroscopy to monitor the nutritive value of animal feeds and the nutritional status of grazing animals.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2000.06a
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• pp.45-45
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• 2000

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1271-1271
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• 2001

Water pollutants in drainage mainly consist of organic compounds. Hence, total organic carbon (TOC), chemical oxygen demand (COD), and biochemical oxygen demand (BOD) were generally used as the indices of pollution. However, these values are determined by special analyzer (TOC), titration method (COD), or microbe culture (BOD). Therefore, the development of simple and easy methods for the determination of water pollution is required. The authors reported the evaluation of water pollution by near infrared (NIR) spectroscopy in a model system with food components (Takamura et al. (200) Near Infrared Spectroscopy: Proceedings of 9th International Conference, pp. 503-507). In this study, the relationship between NIR spectra and drainage was investigated in order to develop a method for evaluation of drainage by NIR. Drainage was obtained in Nara Purification Center. The ranges of TOC, COD, and BOD were 0-130, 0-100 and 0-200, respectively. NIR transmittance spectra were recorded on NIR Systems Model 6250 Research Composition Analyzer in the wavelength range of 680-1235 and 1100-2500 nm with a quartz cell (light path: 0.5, 1, 2, 4 and 10mm) at 10-40. Statistical analysis was performed using NSAS program. A partial least squares (PLS) regression analysis was used for calibration. As the result, a good correlation between the raw NIR spectra and OC was obtained in the calibration. The best light path was 10 and 0.5mm in the wavelength range of 680-1235 and 110-2500nm, respectively. In the calibration, correlation coefficients(R) were 096-0.97 in the both range. In the prediction, however, a good correlation (R=0.89-0.96) was obtained only in the range of 6801235 nm, Similar results were obtained in the cases of COD and BOD. These results suggest the possibility that NIR spectroscopy can be used to evaluate drainage.

• Near Infrared Analysis
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• v.1 no.1
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• pp.31-35
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• 2000

Near-infrared reflectance spectroscopy(NIRS) was used to determine the humic acids in soil samples from the fields of different crops and land-use over Youngnam and Honam regions in Korea. An InfraAlyzer 500 scanning spectrophotometer was obtained near infrared relectance spectra of soil at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid, fulvic acid and its total contents in soils. The raw spectral data(log 1/R) can be used for estimating humic acid, fulvic acid and its total contents in soil by MLR procedure between the content of a given constituent and the spectral response of several bands. In which the predicted results for fulvic acid is the best in the constituents. The new spectral data are converted from the raw spectra by PLSR method such as the first derivative of each spectrum can also be used to predict humic acid and fulvic acid of the soil samples. A low SEC, SEP and a high coefficient of correlation in the calibration and validation stages enable selection of the best manipulation. But a simple calibration and prediction method for determining humic acid and fulvic acid should be selected under similar accuracy and precision of prediction. NIRS technique may be an effective method for rapid and nondestructive determination for humic acid, fulvic acid and its total contents in soils.

• Bulletin of the Korean Chemical Society
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• v.24 no.2
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• pp.246-248
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• 2003

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2000.06a
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• pp.49-49
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• 2000