• Journal of the Korean Applied Science and Technology
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• v.34 no.2
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• pp.210-216
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• 2017

Recovery of low level nitric acid and sulfuric acid ions, which were contained in wastewater of a wet scrubber for de-NOx and de-SOx from ship engines, was attempted as fertilizing materials. This study utilized a selective extraction method using four organic solvents to precipitate the solid salts of ammonium nitrate and ammonium sulfate. The IR analysis showed almost same composition of the extracted ammonium salts with a commercial product, and recovery rate of nitrogen and sulfuric ions was 89% and 80% respectively. It was found that the selectivity and solubility consequently could be the crucial factors to recover the low level ions from the waste scrubbing water.

• Magazine of the Korea Concrete Institute
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• v.7 no.2
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• pp.175-182
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• 1995

Styrene-Maleic anhydride copolymer (SMA) was prepared by the radical copolmerization of styrene and maleic anhydride using ${\alpha}-{\alpha}'$ azobis(isobutyronitrile) as an initiatrr. SMA was further reacted with m-amino phenol to obtain aminophenol-substituted SMR (mSMA). Sulfonated SMA and mSMA were also prepared by the reaction of copolymers with sulfuric acid The copolyniers were characterized by infrared spectroscopy. It was found from the results of elemental analysis that the substitution degree of aminophenol in the mSMR is 44% and the degree is lowered to 35% after sulfonation. The percentage of copolymers adsorbed on the surface of cement particles was increased with a decrease of added copolymers. While, the arnourit of sulfonated SMA absorbed on the surface of cement particles was larger than that of the sulfonated mSMA The copolymers synthesized in this study are probably expected as a high range water reducer for coiicxte.

• Near Infrared Analysis
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• v.1 no.2
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• pp.21-27
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• 2000

Temperature-dependent changes in near-infrared (NIR) spectra have been measured for oleic acid, and nonanoic acid in the pure liquid state. Particular attention has been paid to the 5400-4800 cm$\^$-1/ region where a number of combination bands appear. The NIR spectra of oleic acid show that a band at 5303 cm$\^$-1/ increases with temperature while that at 5270 cm/sup-1/ decreases. It ha been found from their second derivative spectra that these spectral changes take place stepwisely with two break points at 30 and 53$\^{C}$, which correspond to the phase transition temperatures oleic acid reported previously. Principle component analysis (PCA) has been carried out for the NIR spectra of oleic acid in the 5400-4800 cm$\^$-1/ region measured over a temperature range of 15-80$\^{C}$. core plots of the first and second principal components (PCs) show that the NIR spectra are classified into three groups; the spectra measured in the temperature range of 15-30$\^{C}$, those in the range of 31-53$\^{C}$, and those in the range of 54-80$\^{C}$. These temperature ranges correspond to those for quasi-smectic liquid crystal, disordered liquid crystal, and isotropic liquid of oleic acid in the pure liquid state. In other words, PCA provides unambiguous evidence for the phase transitions. similar studies have been carried out for petroselinic acid and nonanoic acid in the pure liquid states, but they do not show any evidence for phase transitions.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.1
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• pp.76-83
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• 2000

This study was carried out to predict blending ratio of cut tobacco(CT), expanded stem(ES), and expanded cut tobacco(ECT) in cigarettes. CT, ES, and ECT samples from A brand were, ground and blended with reference to A blending ratio, and scanned by near infrared spectroscopy(NIRSystem Co., Model 6500). Calibration equations were developed and then determined blending ratio by NIRS. The standard error of calibration(SEC) and performance(SEP) of C factory samples between NIRS and known blending ratio were 0.97%, 1.93% for CT, 0.50%, 1.12 % for ES and 0.68%, 1.10% for ECT, respectively. The SEP of CT, ES and ECT of Band D factory samples determined by C factory calibration equation were more inaccurate than those of C factory samples determined by C factory calibration equations. These results were caused by the difference of CT, ES and ECT spectra followed by each factory. The SEP of CT, ES and ECT of Band D factories determined by calibration equations derived from each factory samples were more accurate than those of determined by calibration equation derived from C factory samples. Each factory SEP of CT, ES and ECT determined by calibration equation derived from all calibration samples(B+C+D factory) was similar to that determined by calibration equation derived from each factory samples. To improve the analytical inaccuracy caused by spectra difference, we need to apply a specific calibration equation for each factory sample. Data in development of specific calibrations between sample and NIRS spectra might supply a method for rapid determination of blending ratio of CT, ES, and ECT.

• Journal of Conservation Science
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• v.28 no.4
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• pp.297-303
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• 2012

Samsebul, the altar portrait behind the statue of Buddha in the main building of Bonghwang temple in Andong, has been designated as Tangible Cultural Property No. 406. These alter portraits have significance as the standard of the research of Samsebul in Joseon period. In this study, fibre of the ground textile is identified using microscopic examination, solubility test, ATR-FT-IR, SEM, XRD. Two samples from Yaksabul(A, B), one sample from Seokgabul(C), and one sample from Amitabul(D), which were collected during the conservation process, were prepared for this study. In previous record, above samples were documented as hemp. Due to severe deterioration and accumulated dust layers on these samples, it was hard to recognize them with naked eyes, but through this study, we could identify that all samples except one from Yaksabul(A) are silk.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1153-1153
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• 2001

Directive 79/373/EEC on the marketing of compound feeding stuffs, provided far a flexible declaration arrangement confined to the indication of the feed materials without stating their quantity and the possibility was retained to declare categories of feed materials instead of declaring the feed materials themselves. However, the BSE (Bovine Spongiform Encephalopathy) and the dioxin crisis have demonstrated the inadequacy of the current provisions and the need of detailed qualitative and quantitative information. On 10 January 2000 the Commission submitted to the Council a proposal for a Directive related to the marketing of compound feeding stuffs and the Council adopted a Common Position (EC N$^{\circ}$/2001) published at the Official Journal of the European Communities of 2. 2. 2001. According to the EC (EC N$^{\circ}$ 6/2001) the feeds material contained in compound feeding stufs intended for animals other than pets must be declared according to their percentage by weight, by descending order of weight and within the following brackets (I :< 30%; II :> 15 to 30%; III :> 5 to 15%; IV : 2% to 5%; V: < 2%). For practical reasons, it shall be allowed that the declarations of feed materials included in the compound feeding stuffs are provided on an ad hoc label or accompanying document. However, documents alone will not be sufficient to restore public confidence on the animal feed industry. The objective of the present work is to obtain calibration equations fur the instanteneous and simultaneous prediction of the chemical composition and the percentage of ingredients of unground compound feeding stuffs. A total of 287 samples of unground compound feeds marketed in Spain were scanned in a FOSS-NIR Systems 6500 monochromator using a rectangular cup with a quartz window (16 $\times$ 3.5 cm). Calibration equations were obtained for the prediction of moisture ($R^2$= 0.84, SECV = 0.54), crude protein ($R^2$= 0.96, SECV = 0.75), fat ($R^2$= 0.86, SECV = 0.54), crude fiber ($R^2$= 0.97, SECV = 0.63) and ashes ($R^2$= 0.86, SECV = 0.83). The sane set of spectroscopic data was used to predict the ingredient composition of the compound feeds. The preliminary results show that NIRS has an excellent ability ($r^2$$\geq$ 0, 9; RPD $\geq$ 3) for the prediction of the percentage of inclusion of alfalfa, sunflower meal, gluten meal, sugar beet pulp, palm meal, poultry meal, total meat meal (meat and bone meal and poultry meal) and whey. Other equations with a good predictive performance ($R^2$$\geq$0, 7; 2$\leq$RPD$\leq$3) were the obtained for the prediction of soya bean meal, corn, molasses, animal fat and lupin meal. The equations obtained for the prediction of other constituents (barley, bran, rice, manioc, meat and bone meal, fish meal, calcium carbonate, ammonium clorure and salt have an accuracy enough to fulfill the requirements layed down by the Common Position (EC Nº 6/2001). NIRS technology should be considered as an essential tool in food Safety Programs.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4107-4107
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• 2001

Previous works have shown the viability of NIRS technology for the prediction of fatty acids in Iberian pig fat, but although the resulting equations showed high precision, in the predictions of new samples important fluctuations were detected, greater with the time passed from calibration development to NIRS analysis. This fact makes the use of NIRS calibrations in routine analysis difficult. Moreover, this problem only appears in products like fat, that show spectrums with very defined absorption peaks at some wavelengths. This circumstance causes a high sensibility to small changes of the instrument, which are not perceived with the normal checks. To avoid these inconveniences, the software WinISI 1.04 has a mathematic algorithm that consist of create a “Repeatability File”. This file is used during calibration development to minimize the variation sources that can affect the NIRS predictions. The objective of the current work is the evaluation of the use of a repeatability file in quantitative NIRS analysis of Iberian pig fat. A total of 188 samples of Iberian pig fat, produced by COVAP, were used. NIR data were recorded using a FOSS NIRSystems 6500 I spectrophotometer equipped with a spinning module. Samples were analysed by folded transmission, using two sample cells of 0.1mm pathlength and gold surface. High accuracy calibration equations were obtained, without and with repeatability file, to determine the content of six fatty acids: miristic (SECV$\sub$without/=0.07% r$^2$$\sub$without/=0.76 and SECV$\sub$with/=0.08% r$^2$$\sub$with/=0.65), Palmitic (SECV$\sub$without/=0.28 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.24% r$^2$$\sub$with/=0.98), palmitoleic (SECV$\sub$without/=0.08 r$^2$$\sub$without/=0.94 and SECV$\sub$with/=0.09% r$^2$$\sub$with/=0.92), Stearic (SECV$\sub$without/=0.27 r$^2$$\sub$without/=0.97 and SECV$\sub$with/=0.29% r$^2$$\sub$with/=0.96), oleic (SECV$\sub$without/=0.20 r$^2$$\sub$without/=0.99 and SECV$\sub$with/=0.20% r$^2$$\sub$with/=0.99) and linoleic (SECV$\sub$without/=0.16 r$^2$$\sub$without/=0.98 and SECV$\sub$with/=0.16% r$^2$$\sub$with/=0.98). The use of a repeatability file like a tool to reduce the variation sources that can disturbed the prediction accuracy was very effective. Although in calibration results the differences are negligible, the effect caused by the repeatability file is appreciated mainly when are predicted new samples that are not in the calibration set and whose spectrum were recorded a long time after the equation development. In this case, bias values corresponding to fatty acids predictions were lower when the repeatability file was used: miristic (bias$\sub$without/=-0.05 and bias$\sub$with/=-0.04), Palmitic (bias$\sub$without/=-0.42 and bias$\sub$with/=-0.11), Palmitoleic (bias$\sub$without/=-0.03 and bias$\sub$with/=0.03), Stearic (bias$\sub$without/=0.47 and bias$\sub$with/=0.28), oleic (bias$\sub$without/=0.14 and bias$\sub$with/=-0.04) and linoleic (bias$\sub$without/=0.25 and bias$\sub$with/=-0.20).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.spc
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• pp.108-114
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• 2008

Near infrared spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. The applicability of near infrared reflectance spectroscopic method was tested to determine the color value (L, a, b) of green tea. A total of 162 green tea calibration samples and 82 validation samples were used for NIRS equation development and validation, respectively. In the developed NIRS equation for analysis of the color value (L, a, b), the most accurate equation for L value was obtained at 2, 8, 6, 1 (2nd derivative, 8 nm gap, 6 points smoothing, and 1pointsecond smoothing), and for a, and b value were obtained at 1, 4, 4, 1 (1st derivative, 4 nm gap, 4points smoothing, and 1 point second smoothing) math treatment condition with SNVD (Standard Normal Variate and Detrend) scatter correction method and entire spectrum ($400{\sim}2,500\;nm$) by using MPLS (Modified Partial Least Squares) regression. Validation results of these NIRS equations showed very low bias (L: 0.005%, a: 0.003%, b: -0.013%) and standard error of prediction (SEP, L: 0.361%, a: 0.141%, b: 0.306%) as well as high coefficient of determination ($R^2$, L: 0.905, a: 0.986, b: 0.931). Therefore, these NIRS equations can be applicable and reliable for determination of color value (L, a, b) of green tea, and NIRS method could be used as a mass screening technique for breeding programs and quality control in the green tea industry.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.5
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• pp.489-494
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• 1994

Near Infrared Reflectance Spectroscopy(NIRS) has been used as a tool for the rapid, accurate, protein assay of malting barley. NIRS used in this study was filter type instruments, Neotec 102. The objective of this study was to obtain the best calibration equation, for the rapid, ease and accurate protein content analysis of malting barley using NIRS system. The optimum wavelength for protein content analysis used NIRS were 2095nm, 2095/1941nm, 2095/1941/2282nm, 2905/1941/2282/2086nm, respectively. Mean protein content with this calibration equation in NIRS analysis was 10.59%, while 10.60% in Micro-Kjeldahl one. The range of protein content in Micro-Kjeldahl was 8.66~12.66% and that in NIRS was 8.80~12.35%. When 18 other varieties produced in 1992 were analysed with 2095nm, 2095/1941nm, 2095/1941/2282nm, 2095/1941/2282/2086nm equation, standard deviation of difference (SDD)and standard error of performence(SEP) and $R^2$ values were 0.47, 0.43, 0.95, respectively. Both the mean protein content by Micro-Kjeldahl and by NIRS was 10.25%. With this equation, analysied 31 varities produced in 1993, SDD and SEP and r values were 0.69, 0.67, 0.91, respectively, and that bias value was 0.65. In this analysis, mean protein content by Micro-Kjeldahl was 10.17% and by NIRS was 10.81%. The range of protein content in Micro-Kjeldahl was 7.58~14.29%, What that in NIRS was 8.63~13.93%. After adjusted bias in the best calibration equation, mean protein content of Micro-Kjeldahl was 10.17% and that of NIRS was 10.09%, without variance of SDD, SEP and r values.