• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.111-116
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• 2012

Nondestructive evaluation of seed viability is one of the highly demanding technologies for seed production industry. Conventional seed sorting technologies, such as tetrazolium and standard germination test are destructive, time consuming, and labor intensive methods. Near infrared spectroscopy technique has shown good potential for nondestructive quality measurements for food and agricultural products. In this study, FT-NIR spectroscopy was used to classify normal and artificially aged lettuce seeds. The spectra with the range of 1100~2500 nm were scanned for lettuce seeds and analyzed using the principal component analysis(PCA) method. To classify viable seeds from nonviable seeds, a calibration modeling set was developed with a partial least square(PLS) method. The calibration model developed from PLS resulted in 98% classification accuracy with the Savitzky-Golay $1^{st}$ derivative preprocessing method. The prediction accuracy for the test data set was 93% with the MSC(Multiplicative Scatter Correction) preprocessing method. The results show that FT-NIR has good potential for discriminating non-viable lettuce seeds from viable ones.

• Korean Journal of Agricultural Science
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• v.28 no.2
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• pp.116-124
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• 2001

The measurement values of proximate composition in fresh ginseng could provide the important information for red ginseng processing. The measurement of them were performed by near-infrared (NIR) spectroscopy. Linear regression model for the predicting of proximate composition was developed and validated. The regression values of moisture, crude starch, crude ash, crude fiber, calcium, and magnesium contents were shown as 0.918, 0.951, 0.897, 0.728, 0.933, and 0.390, respectively. Therefore, the proximate composition of fresh ginseng could be measured by NIR, feasibly.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.1
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• pp.44-49
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• 2021

Recently, infrared (IR) and near-infrared (NIR) light-emitting diodes (LEDs) were widely used for home medical applications owing to its low output power and wide exposed area for curing. For deep penetration of the light under the skin, multiple LEDs with wavelengths of 700~10,000 nm were located on a flexible printed circuit board. When multiple wavelengths of LEDs were soldered on a circuit board, the lifetime of LED module highly depends on LEDs with a short lifetime. The mean time to failure (MTTF) was able to calculate with the experimental results under high temperature and the Arrhenius model. The results of this study could help companies to approve the warranty of LED modules and its product.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.44.4-44.4
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• 2019

The supernova remnant Cassiopeia A (Cas A) provides a unique opportunity to observe the fine details of the explosion of core-collapse supernova (SN). Previous optical and near-infrared (NIR) observations of Cas A have shown that the spatial distribution of the metal-enriched SN ejecta is very complicated, indicating that the SN explosion should have been asymmetric and turbulent, especially near the core. Recently, we obtained a long-exposure (~10 hr) image of Cas A by using the UKIRT 3.6-m telescope with a narrow-band filter centered at [Fe II] 1.644 um emission. This 'deep [Fe II] image' provides an unprecedented panoramic view of Cas A, revealing the distribution of dense SN ejecta over the entire remnant. We have carried out NIR multi-object spectroscopic observations of the dense ejecta knots in the northeastern (NE) and eastern (E) outer regions of the remnant using the MMIRS attached on the MMT 6.5-m telescope. A total of 67 ejecta knots are detected. By analyzing their spectra, we have found that the knots in the NE area show strong [S II]/[S III] and [Fe II] lines but little or no [P II] line, while those in the E outer region show strong [Fe II] lines but weak [S II]/[S III] lines. In this talk, we present the preliminary results of our NIR spectroscopic observations and discuss the implications.

• Clean Technology
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• v.18 no.1
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• pp.31-37
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• 2012

Biomass has become a major feedstock for bioenergy and other bio-based products because of its renewability and environmental benefits. Various researches have been done in the prediction of crucial characteristics of biomass, including the active utilization of spectroscopy data. Near infrared (NIR) spectroscopy has been widely used because of its attractive features: it's non-destructive and cost-effective producing fast and reliable analysis results. This work developed the multivariate statistical scheme for predicting weight loss profiles based on the utilization of NIR spectra data measured for six lignocellulosic biomass types. Wavelet analysis was used as a compression tool to suppress irrelevant noise and to select features or wavelengths that better explain NIR data. The developed scheme was demonstrated using real NIR data sets, in which different prediction models were evaluated in terms of prediction performance. In addition, the benefits of using right pretreatment of NIR spectra were also given. In our case, it turned out that compression of high-dimensional NIR spectra by wavelet and then PLS modeling yielded more reliable prediction results without handling full set of noisy data. This work showed that the developed scheme can be easily applied for rapid analysis of biomass.

• Analytical Science and Technology
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• v.30 no.5
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• pp.234-239
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• 2017

Identifying the components of residues that are not completely burned at the sites of fires site can provide valuable information for tracing the causes of fires. In order to clarify the types of plastic combustion residues found at the scenes of fires, we studied the residue formed after the combustion of polyethylene (PE) and acrylonitrile butadiene styrene (ABS). Plastic samples were burned at 200, 300, 350, 400, and $500^{\circ}C$ for 3 min using a cone calorimeter, and the changes in weight and combustion products were observed. The powder products obtained by lyophilization and pulverization of the combustion products obtained at each temperature were analyzed by a Fourier transform-near infrared (FT-NIR) spectrometer. When the PE samples were burned, the weight did not change up to $350^{\circ}C$, however a significant change in the weight could be measured above $400^{\circ}C$. The principal component analysis (PCA) of the FT-NIR spectra of the PE and ABS samples obtained at each temperature confirmed that the combustion residues at each temperature were PE and ABS, respectively. Therefore, the types of unburned plastics found at the sites of fires can be confirmed rapidly by near infrared spectroscopy.

• Journal of the Korean Wood Science and Technology
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• v.44 no.6
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• Journal of the Korean Wood Science and Technology
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• v.45 no.2
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.203-208
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• 2007

Drying characteristics are confirmed by experiment to a printing machine which use Gravure ink or metal ink for an optimum design of direct radiation drying system room using NIR. As a result, Drying is easily accomplished in short distance and low moving speed in Gravure ink, but drying is dropped in metal ink because of oil. This confirmed that the development of water metal ink had to be proceeded to accomplish a perfect drying condition.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1253-1253
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• 2001

The ability to accurately assess wine quality is important during the wine making process, particularly when allocating batches of wines to styles determined by consumer requirements. Grape payments are often determined by the quality category of the wine that is produced from them. Wine quality, in terms of sensory characteristics, is normally a subjective measure, performed by experienced winemakers, wine competition judges or winetasting panellists. By nature, such assessments can be biased by individual preferences and may be subject to day-to-day variation. Taste and aroma compounds are often present in concentrations below the detection limit of near infrared (NIR) spectroscopy but the more abundant organic compounds offer potential for objective quality grading by this technique. Samples were drawn from one of Australia's major wine shows and from BRL Hardy's post-vintage wine quality allocation tastings. The samples were scanned in transmission mode with a FOSS NIR Systems 6500, over the wavelength range 400-2500 ㎚. Data analysis was performed with the Vision chemometrics package. With samples from the allocation tastings, the best correlations between NIR spectra and tasting data were obtained with dry red wines. These calibrations used loadings in the wavelengths related to anthocyanins, ethanol and possibly tannins. Anthocyanins are a group of compounds responsible for colour in red wines - restricting the wavelengths to those relating to anthocyanins produced calibrations of similar accuracy to those using the full wavelength range. This was particularly marked with Merlot, a variety that tends to have relatively lower anthocyanin levels than Cabernet Sauvignon and Shiraz. For dry white wines, calibrations appeared to be more dependent on ethanol characteristics of the spectrum, implying that quality correlated with fruit maturity. The correlations between NIR spectra and sensory data obtained using the wine show samples were less significant in general. This may be related to the fact that within most classes in the show, the samples may span vintages, glowing areas and winemaking styles, even though they may be made from only one grape variety. For dry red wines, the best calibrations were obtained with a class of Pinot Noir - a variety that tends to be produced in limited areas in Australia and would represent the least matrix variation. Good correlations were obtained with a tawny port class - these wines are sweet, fortified wines, that are aged for long periods in wooden barrels. During the ageing process Maillard browning compounds are formed and the water is lost through the barrels in preference to ethanol, producing “concentrated” darkly coloured wines with high alcohol content. These calibrations indicated heaviest loadings in the water regions of the spectrum, suggesting that “concentration” of the wines was important, whilst the visible and alcohol regions of the spectrum also featured as important factors. NIR calibrations based on sensory scores will always be difficult to obtain due to variation between individual winetasters. Nevertheless, these results warrant further investigation and may provide valuable Insight into the main parameters affecting wine quality.