• 한국연초학회지
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• 제20권2호
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• pp.183-190
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• 1998

This study was conducted to analyze chemical components in flue-cured tobacco using near infrared spectroscopy(NIRS). Samples were collected in '96 and '97 crop year and were scanned in the wavelengths of 400 ～ 2500 nm by near infrared analyzer(NIRSystem Co., Model 6500). Calibration equations were developed and then analyzed flue-cured samples by NIRS. The standard error of calibration(SEC) and performance (SEP) of '96 crop year samples between NIRS and standard laboratory analysis(SLA) were 0.18% and 0.24% for nicotine, 1.60% and 1.77% for total sugar, 0.13% and 0.15% for total nitrogen, 0.58% and 0.68% for crude ash, 0.23% and 0.28% for ether extracts, and 0.09% and 0.08% for chlorine, respectively. The coefficient of determination($R^2$) of calibration and prediction samples between NIRS and SLA of '96 crop year samples was 0.94～0.99 and 0.83～0.97 depending on chemical components, respectively. The SEC and SEP of '97 crop year samples were similar to those of '96 crop year samples. The SEP of '97 crop year samples which were analyzed using '96 calibration equation was 0.32 % for nicotine, 2.72% for total sugar, 0.14 % for total nitrogen, 1.00 % for crude ash, 0.48 for ether extracts and 0.17% for chlorine, respectively. The prediction result was more accurate when calibration and prediction samples were produced in the same crop year than those of the different crop year. The SEP of '96 and '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was similar to that of '96 crop year samples using 96 calibration equation and that of '97 crop year samples using '97 calibration equation, respectively. The SEP of '97 crop year samples using calibration equation which was developed '96 plus '97 crop year samples was lower than that of '97 crop year samples analyzed by '96 calibration equation. To improve the analytical inaccuracy caused by the difference of crop year between calibration and prediction samples, we need to include the prediction sample spectra which are different from calibration sample spectra in recalibration sample spectra, and then develop recalibration equation. Although the analytical result using NIR is not as good as SLA, the chemical component analysis using NIR can apply to tobacco leaves, leaf process or tobacco manufacturing process which demand the rapid analytical result.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.

• 대한화학회지
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• 제47권5호
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• pp.447-459
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• 2003

일반화된 이차원 상관 분광학은 모든 분자 분광학 즉, 적외선 (infrared, IR), 근적외선 (near-infrared, NIR), 라만 (Raman) 및 형광 (fluorescence) 분광학뿐만 아니라 X-ray 회절, X-ray 흡수 분광학 (XAS), 크로마토그래피 (chromatography) 등에 적용되어 시간뿐만 아니라 온도, 압력, 농도, 조성과 같은 다른 물리적 변화인 외부 섭동 (perturbation) 아래에서 얻은 스펙트럼 분석의 새로운 분광학으로 다양한 분야의 연구가 활발히 진행 중이다. 또한 같은 외부 섭동 아래에서 얻은 완전히 다른 두 스펙트럼의 2D hetero-spectral correlation analysis가 가능하므로 다양한 분야 즉, 생체 물질, 고분자, 나노입자 등의 연구가 활발히 진행 중이다. 이런 다양한 분야의 응용성 때문에 ？일반？?이차원 상관 분광학？？물리, 분석, 고분자, 나노물질 및 생화학 연구에 새로운 방향을 제시할 수 있을 뿐만 아니라 바이오 나노기술 연구에 상승 효과를 제공할 수 있다. 본 논문은 "일반화된 이차원 상관 분광학"의 원리와 그 다양한 응용성을 본 저자들의 연구를 중심으로 소개하고자 한다.

• 천문학회보
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• 제35권2호
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• pp.68.1-68.1
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• 2010

Cassiopeia A supernova remnant is a young (~330 yr) remnant of Type IIb SN explosion with a massive progenitor. It shows two distinct optical knots; fast moving ejecta knots (FMKs) and quasi stationary circumstellar knots (QSFs). These knots offer an unique opportunity to explore the details of the explosion and also the end state evolution of the Type IIb SN progenitor. We have obtained NIR long-slit (30") spectra of 7 positions around the bright rim of Cas A in [Fe II] 1.644 micron using Triplespec which is a cross-dispersed near-infrared spectrograph that provides continuous wavelength coverage from 0.95-2.46um at intermediate resolution of 2700. Most of the FMKs show strong sulfur, silicon, and iron forbidden lines but no hydrogen or helium lines. The QSFs, on the other hand, show a much richer spectrum with strong hydrogen, helium, and iron lines, but no sulfur and silicon lines. We measure their fluxes and radial velocities, and derive their physical parameters such as electron density and temperature. We also measure the proper motion of these knots from two [Fe II] 1.644 micron images obtained at 3-year interval. We analyze the physical properties of these knots and discuss the evolution and explosion of the progenitor of Cas A.

• 천문학회보
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• 제38권1호
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• pp.49.1-49.1
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• 2013

We have been carrying out near-infrared (NIR) spectroscopy as well as [Fe II] narrow band imaging observations of Cassiopeia A supernova remnant (SNR). In this presentation, we describe the spectral classification of the iron knots around the SNR. From eight long-slit spectroscopic observations for the iron-bright shell, we identified a total of 61 iron knots making use of a clump-finding algorithm, and performed principal component analysis in an attempt to spectrally classify the iron knots. Three major components have emerged from the analysis; (1) Iron-rich, (2) Helium-rich, and (3) Sulfur-rich groups. The Helium-rich knots have low radial velocities (${\mid}v_r{\mid}$ < 100 km/s) and radiate strong He I and [Fe II] lines, that match well with Quasi-Stationary Flocculi (QSFs) of circumstellar medium, while the Sulfur-rich knots show strong lines of oxygen burning materials with large radial velocity up to +2000 km/s, which imply that they are supernova ejecta (i.e. Fast-Moving Knots). The Iron-rich knots have intermediate characteristics; large velocity with QSF-like spectra. We suggest that the Iron-rich knots are missing "pure" iron materials ejected from the inner most region of the progenitor and now encountering the reverse shock.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3124-3124
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• 2001

The development and evolution of near infra-red spectroscopic (NIS) calibrations for high-moisture materials is an expensive proposition. Such investment is suspect unless the instrument, or instruments, on which calibrations were developed can be preserved intact or re-standardized as component replacements occurs. The objective of this paper is to detail the changes in performance of a six-year old instrument after maintenance in years five and six resulted in collection of spectral data that was increasingly removed from the calibration population. Calibrations for the analysis of mature sugarcane stalks, a high-moisture material, were developed successfully in 1995 using a broad sample population in terms of genetics, and spectral and temporal variation. The spectral library was further broadened in 1996. In 1997, 1999, 1999, and 2000, additional samples constituting 10% of the laboratories throughput were subjected to full component analyses using routine laboratory techniques. These samples were primarily random samples, but were complemented with samples that were significant for the spectral H statistic or for the component t statistic. In 1998, an additional calibration was developed for populations consisting of samples of either mature stalks (culms) or sucker culms. Substantial additional samples numbers were collected for this calibration in 1999 and 2000. Attempts to standardize the scanning spectrophotometer used for these calibrations with a second similar instrument in 1999 failed because the instruments were optically different, and standardization could not account for this. Maintenance adjustments were made to the remote reflectance probe of the original instrument in 1999, and replacement of its PbS detectors was done in 2000. Spectral data collected in 1999 and 2000 yielded spectral populations that were increasingly removed from the respective spectral populations on which the calibrations were developed. The mature stalk calibrations benefited marginally from evolutionary calib.

• Journal of Pharmaceutical Investigation
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• 제39권1호
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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.

• 한국지능시스템학회논문지
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• 제26권5호
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• pp.416-422
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• 2016

수많은 플라스틱이 산업분야에 다양하게 사용되어지고 있다. 또한 많은 양의 플라스틱 폐기물들이 발생하고 있다. 재활용에 대한 연구는 환경오염 뿐만아니라 한정된 유용한 자원이 버려지는 것을 방지하기 위해 중요한 이슈로 부각되고 있다. 이렇기 때문에 폐플라스틱의 재활용은 재사용 관점에서 주목받고 있는 실정이다. 현재 재활용 센터에서는 플라스틱의 재질을 분류하기 위해 NIR 센서를 이용한 플라스틱 자동 분류 시스템을 구축 및 운용하고 있다. 하지만 흑색 플라스틱은 여전히 분류가 되지 않는 도전적인 목표로 남아있다. 카본 블랙이 포함된 흑색 플라스틱의 경우 검정색의 특성상 NIR 장비에서 나오는 빛을 흡수하기 때문에 분류에 어려움이 있다. 본 연구는 NIR 장비 대신 흑색 플라스틱을 분류하는 방법에 대한 연구이다. 흑색 플라스틱의 정성적, 정량적 분석을 위해 Raman 분광법을 사용하였다. 또한 분류기의 인식률을 높이기 위해 데이터를 특성을 분석하고 흑색 플라스틱을 좀 더 확실하게 분류하기 위해 Support Vector Machine(SVM), 주성분 분석법(PCA) 같은 알고리즘을 이용하였다.

• 환경생물
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• 제39권4호
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• pp.581-589
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• 2021

본 연구는 메꽃과 6종의 식물에 대해 신속하고 비파괴적으로 분류하기 위해 근적외선(Vis-NIR) 스펙트럼을 이용하였고 데이터의 전처리와 머신러닝 기술을 적용하였다. 전국적으로 분포하는 메꽃과 6종에 대해 야외에서 휴대용 분광기를 이용하여 판별하였다. 식물의 잎의 표면에서 400~1,075 nm의 근적외선 스펙트럼(1.5 nm)을 수집하였다. 수집된 스펙트럼 데이터는 3가지의 전처리와 raw데이터를 이용하였고 4종류의 머신러닝 모델을 적용하여 높은 판별 정확도를 확인하였다. 전처리와 머신러닝 모델의 조합을 통해 분석된 판별의 정확도는 43~99%의 범위로 분석되었고, standard normal variate 전처리와 support vector machine 머신러닝 모델의 조합에서 판별 정확도가 98.6%로 가장 높게 나타났다. 본 연구에서 수집된 스펙트럼은 식물의 성장단계, 다양한 측정 지역 및 잎에서의 측정 위치 등과 같은 요인과 더불어 데이터 분석을 위한 조건으로 최적의 전처리와 머신러닝 기술을 적용한다면 메꽃과 식물의 야외에서의 정확한 분류가 가능하고 이들 식물의 효과적인 관리와 모니터링에 활용할 수 있을 것으로 판단되었다.