• YAKHAK HOEJI
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• v.46 no.5
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• pp.324-330
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• 2002

This experiment was carried out to determine non-destructively the hydrogen peroxide concentration of 3％ antiseptic hydrogen peroxide solutions by portable near-infrared (NIR) system. Hydrogen peroxide standards were prepared ranging from 0 to 25.6 w/w％ and the NIR spectra of hydrogen peroxide standard solutions were collected by using a quartz cell in 1 mm pathlength. We found the variation of absorbance band due to OH vibration of hydrogen peroxide depending on the concentration around 1400 nm in the second derivatives spectra. Partial least square regression (PLSR) and multilinear regression (MLR) were explored to develop a calibration model over the spectral range 1100-1720 nm. The model using PLSR was better than that using MLR. The calibration showed good results with a standard error of prediction (SEP) of 0.16％. In order to validate the developed calibration model, routine analyses were performed using commercial antiseptic hydrogen peroxide solutions. The hydrogen peroxide values from the NIR calibration model were compared with the values from a redox titration method. The NIR routine analyses results showed good correlation with those of the redox titration method. This study showed that the rapid and non-destructive determination of hydrogen peroxide in the antiseptic solution was successfully performed by portable NIR system without very harmful solvents.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1612-1612
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• 2001

The production of grain for export and domestic use is one of Australia's most important agricultural industries, and the NIR technique has been used extensively over many years for the routine monitoring of grain quality, particularly moisture and protein content. Because most Australian grain is intended for human food production, the determinants of grain quality for livestock feed, apart from protein, have been largely ignored. However the increasing use of grain for feeding to pigs, poultry, beef cattle and dairy cows has led to an important national research project entitled “Premium Grains for Livestock”. Two of the objectives of this project are to determine the compositional and functional characteristics of grains which influence their nutritional quality for the various classes of livestock, and to adopt rapid and objective analytical tests for these quality criteria. NIR has been used in this project firstly to identify a set of grain samples from a large population of breeders' lines which showed a wide spectral variation, and hence a potentially wide variation in nutritional value. The selected samples were not only subjected to an extensive array of chemical, physical and in vitro analyses, but also were grown out to produce sufficient quantities of grain to feed to animals in vivo studies. Additional grains were also strategically selected from farms in order to include the effect of weather damage, such as rain, drought and frost. In this study to date, NIR calibrations have been derived or attempted, on both ground and whole grains, for in vivo dry matter digestibility (DMD), pepsin-cellulase dry matter disappearance, protein, fat, acid detergent fibre, neutral detergent fibre, starch, in sacco DMD and in vitro assays to simulate starch digestion in the lumen and small intestine. Results so far indicate high calibration accuracy for chemical components (SECV 0.3 to 2.6%) and very promising statistics for in vivo DMD (SECV 1.8, $R^2$ 0.93, SD 7.0, range 61.9 to 92.3, n=60). There appears to be some potential for NIR to estimate some in vitro properties, depending upon the accuracy of reference methods and appropriate sample populations. Current work is in progress to extend the range of grains with in vivo DMD values (a very laborious and expensive process) and to increase the robustness of the various NIR calibrations, with the aim of implementing uniform testing procedures for nutritional value of grains throughout Australia.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• Journal of Pharmaceutical Investigation
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• v.39 no.1
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• pp.29-36
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• 2009

Since the quality of final products is significantly affected by the homogeneity of powder mixture, the powder blending process has been regarded as one of the critical pharmaceutical unit processes, especially for solid dosage forms. Accordingly, the monitoring to determine a blending process' end-point based on a faster and more accurate in-line/on-line analysis has attracted enormous attentions recently. Among various analytical tools, NIR (near-infrared) spectroscopy has been extensively studied for PAT (process analytical technology) system due to its many advantages. In this study, NIR spectroscopy was employed with an optical fiber probe for the in-line monitoring of fluid-bed blending process. The position of the probe, the ratio of binary powder mixture, the powder size differential and the back-flush period of the shaking bag were examined as principal process parameters. During the blending process of lactose and mannitol powders, NIR spectra were collected, corrected, calibrated and analyzed using MSC and PLS method, respectively. The probe position was optimized. A reasonable end-point was predicted as 1,500 seconds based on 5% RSD value. As a consequence, it was demonstrated that the blending process using a fluid-bed processor has several advantages over other methods, and the application of NIRS with an optical fiber probe as PAT system for a fluid-bed blending process could be high feasible.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.416-422
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• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.187-193
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• 2012

AKARI has 4 imaging bands in the far-infrared (FIR) and 9 imaging bands that cover the near-infrared (NIR) to mid-infrared (MIR) contiguously. The FIR bands probe the thermal emission from sub-micron dust grains, while the MIR bands observe emission from stochastically-heated very small grains and the unidentified infrared (UIR) band emissions from carbonaceous materials that contain aromatic and aliphatic bonds. The multi-band characteristics of the AKARI instruments are quite efficient to study the spectral energy distribution of the interstellar medium, which always shows multi-component nature, as well as its variations in the various environments. AKARI also has spectroscopic capabilities. In particular, one of the onboard instruments, Infrared Camera (IRC), can obtain a continuous spectrum from 2.5 to $13{\mu}m$ with the same slit. This allows us to make a comparative study of the UIR bands in the diffuse emission from the 3.3 to $11.3{\mu}m$ for the first time. The IRC explores high-sensitivity spectroscopy in the NIR, which enables the study of interstellar ices and the UIR band emission at $3.3-3.5{\mu}m$ in various objects. Particularly, the UIR bands in this spectral range contain unique information on the aromatic and aliphatic bonds in the band carriers. This presentation reviews the results of AKARI observations of the interstellar medium with an emphasis on the observations of the NIR spectroscopy.

• Carbon letters
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• v.10 no.1
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• pp.9-13
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• 2009

We propose an evaluation method of the relative content of single-walled carbon nanotubes (SWCNT) in SWCNT soot synthesized by arc discharge using UV-VIS-NIR absorption spectroscopy. In this method, we consider the absorbance of semiconducting and metallic SWCNTs together to calculate the relative content of SWCNTs with respect to a highly purified reference. Our method provides the more reliable and realistic evaluation of SWCNT content with respect to the whole carbonaceous content than the previously reported method.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.477-481
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• 2007

Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression were used to predict the amylose content of polished rice. Spectral reflectance data in a wavelength range of 1,000 to 2,500 nm were obtained with a commercial spectrophotometer for 60 different varieties of Korean rice. For a comparison of this spectroscopic method to a standard chemical analysis, the amylose contents of the tested rice samples were determined by the iodine-blue colorimetric method. The highest correlation for the rice amylose ($R^2=0.94$, standard error of prediction=0.20% amylose content) was obtained when using the FT-NIR spectrum data pre-treated with normalization, the first derivative, smoothing, and scattering correction.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1123-1123
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• 2001

In recent years, a miniature spectrometer has been extensively developed due to the marriage of fiber optics and semiconductor detector array. This type of miniature spectrometer has advantages of low price and robustness due to the capability of mass production and no moving parts are required such as lenses, mirrors and scanning monochromator. These systems are ideal for use in teaching labs, process monitoring and field analyses. A portable near infrared (NIR) system has been developed for qualitative and quantitative analysis. This system includes a tungsten halogen lamp for light source, a fiber optics connected a light source, and a sample module to the microspectrometer, The size of spectrometer can be as small as 2.5 cm x 1.5 cm x 0.1 cm. Wavelength ranges can be chosen as 360-800 nm, 800-1100 nm and 1100-1900 nm depending on the type of detector. The software consists of various tools for multivariate analysis and pattern recognition techniques. To evaluate the system, long and short-term stability, wavelength accuracy, and stray light have been investigated and compared with conventional scanning type NIR spectrometer. This developed system can be sufficiently used for quantitative and qualitative analysis for various samples such as agricultural product, herbal medicine, food, petroleum, and pharmaceuticals, etc.