• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.121-125
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• 2009

농업과 환경분야에서 토양 상태를 신속하고 주기적으로 모니터링하는 것에 대한 관심이 높아지고 있다. 토양의 특성을 측정하는 기존의 화학분석 방식은 분석의 정밀도, 시료의 수, 분석항목 등에 따라 시간, 인력, 비용적 소모가 커진다. 최근에는 식품, 농업, 환경 분야에서 신속하고 비파괴적 분석 방법으로 가시 근적외선 분광학을 도입하고 있다. 가시 근적외선 영역(VNIR, 400-2400 nm)에는 다양한 물질의 고유한 흡수분광형태가 존재한다는 이론적 토대로부터 물질의 정성 정량적 분석이 가능하다고 알려져 있다. 본 연구에서는 VNIR 분광 스펙트럼으로부터 Al, organic carbon (OC), clay, silt, sand, CEC (Cation exchange capacity), CEC/clay 등의 토양 특성을 정량하고자 하였다. 농경지에서 채취한 94개 토양시료를 기존의 화학분석 방법으로 분석하고 실내에서 VNIR 스펙트럼을 측정하였다. 스펙트럼은 원시형태와, 1차, 2차 도함수로 변환된 형태 모두 partial least square regression (PLSR) 모델에 적용하였다. PLSR에 의한 토양특성 추정식은 RMSE, $R^2$, SDE, RPD 값을 이용하여 검증하였다. Al, OC, silt, sand 함량에 대해서는 통계적으로 유의한 수준의 추정값을 산출하였고, clay와 CEC/clay에 대해 추정한 값은 실측값과 약한 상관성을 나타내었다. 이러한 분광학적인 추정 기법은 영상을 이용한 정성 정량분석에 활용될 수 있을 것으로 사료된다.

• Clean Technology
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• v.18 no.3
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• pp.265-271
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• 2012

The use of renewable energies has been required to diminish the dependency on fossil fuels. As one of clean energy sources biomass has been extensively studied because various biomass resources necessitated rapid characterization of their chemical and physical properties in an on-line or real-time basis. For such an analysis near-infrared (NIR) spectroscopy has been successfully applied because of its non-invasive and informative characteristics. In this work, the applicability of nonlinear chemometric techniques based on biomass near infrared (NIR) data is evaluated for the rapid prediction of ash/char contents in different types of biomass. The prediction results of various prediction models and the effect of using preprocessing methods for NIR data are compared using six types of biomass NIR data. The results showed that nonlinear prediction models yielded better prediction performance than linear ones. It also turned out that by adopting the use of proper preprocessing methods the performance of prediction of biomass properties improved.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.87-87
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• 2017

농산물의 품질 및 성분을 측정하는데 있어 기존의 화학적 분석 방식은 정밀도가 높으나 측정에 소요되는 시간과 비용이 많이 들어, 현장 적용하기에는 한계가 있다. 일반적으로 근적외선 분광 분석(Near Infra Red Spectroscopy, NIRS) 방법은 가공 과정에 따라 빠르게 변화되는 단백질 조성 및 수분함량 측정 등에 이용되고 있다. 분석에 소요 시간이 많이 걸리는 켈달법(Kjeldahi method)에 비해 NIR 분광 분석을 통한 보정으로 연속적인 모니터링이 가능하다. 본 연구에서 사용된 시료를 고정시키기 위한 프레임을 제작한 후 NIR센서와 광원인 LED의 각도를 고정시키고 측정 대상체인 사절된 감자 크기에 따라 시료를 고정시킬 수 있는 프레임을 반사면에 위치시켰다. 확산 반사법을 이용하여 프레임에 씨감자 시료를 고정 시킨 후 백색 LED를 이용하여 감자 표면에 빛을 반사시켜 3일 동안 12시간 마다 해당 시료들(열처리, 비누용액 침지, 생감자)의 스펙트럼을 측정하였다. 해당 시료들은 측정 기간 동안 저온상태($4^{\circ}C$)와 실온상태($20^{\circ}C$)에서 보관되었다. 실험 결과는 파장대 145nm에서 저온상태에서 보관된 생감자는 시간경과에 따른 흡광도의 결정 계수값($r^2$)은 0.98 이었다. 이는 감자가 저온에서 생감자의 상태 변화가 일어나고 있다는 것을 의미하고 파장대 145nm에서 시간에 따른 저온상태에서 보관한 감자의 상태 변화 예측이 가능함을 의미한다. 비누용액에 침지시킨 후 실온에 보관한 감자는 시간이 경과함에 따라 파장이 증가함에 따라 흡광도가 증가하였다. 이는 감자에 들어있는 Polyphenol Oxidase 함량 변화로 갈변 현상이 일어난 것을 알 수 있다. 또한 실온에서 보관한 생감자도 시간 경과에 따라 갈변 현상이 일어났지만 용액에 침지시킨 감자보다는 갈변 현상이 36시간 이후로 발견되었다. 열처리 후 실온에서 보관한 감자의 경우에는 갈변현상이 나타나지 않았다. 저온상태에서 보관한 감자시료들 모두 갈변형상이 나타나지 않았지만, 24시간이 지난 후 용액에 침지시킨 감자는 갈변 현상이 발생되었다. 생감자와 열처리한 감자는 시간 경과에 따른 갈변현상이 일어나지 않았으므로, 감자의 갈변현상은 감자의 표면 처리 방법에 국한되지 않고 온도에 영향을 더 많이 받는다는 것을 나타내고 있다. 본 연구는 향후 감자의 품질 및 성분 측정에서 간편하게 사용될 수 있는 감자의 품질 계측 기술에 기여할 것으로 판단된다.

• Journal of Animal Environmental Science
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• v.13 no.2
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• pp.113-120
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• 2007

This study was conducted to measure Nitrogen(N), Phosphate($P_2O_5$), Potassium ($K_2O$), Organic matter(OM) and Moisture content of liquid pig manure by Near Infrared Spectroscopy(NIRS) and to develop an alternative and analytical instrument which are used for measurement of N, $P_2O_5$, $K_2O$, OM, and Moisture contents for liquid pig manure. The liquid pig manure sample's transmittance spectra were measured with a NIRS in the wavelength range of 400 to 2,500 nm. Multiple linear regression and partial least square regression were used for calibrations. The correlation coefficient(RSQ) and standard error of calibration(SEC) obtained for nitrogen were 0.9190 and 2.1649, respectively. The RSQ for phosphate, potassium, organic matter and moisture contents were 0.9749, 0.5046, 0.9883 and 0.9777, and the SEC were 0.5019, 1.9252, 0.1180 and 0.0789, respectively. These results are indications of the rapid determination of components of liquid pig manure through the NIR analysis. The simple analytical instrument for liquid pig manure consisted of a tungsten halogen lamp for light source, a sample holder, a quartz cell, a SM 301 spectrometer for spectrum analyzer, a power supply, an electronics, a computer and a software. Results showed that the simple analytical instrument that was developed can approximately predict the phosphate, organic matter and moisture content of the liquid pig manure when compared to the analysis taken by NIRS. The low predictability value of potassium however, needs further investigation. Generally, the experiment proved that the simple analytical instrument was reliable, feasible and practical for analyzing liquid pig manure.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.235-244
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• 2016

In large-area crop classification with MODIS data, a mixed pixel problem caused by the low resolution of MODIS data has been one of main issues. To mitigate this problem, this paper proposes a hierarchical classification algorithm that selectively classifies the specific crop class of interest by using their spectral characteristics. This selective classification algorithm can reduce mixed pixel effects between crops and improve classification performance. The methodological developments are illustrated via a case study in Jilin city, China with MODIS Normalized Difference Vegetation Index (NDVI) and Near InfRared (NIR) reflectance datasets. First, paddy fields were extracted from unsupervised classification of NIR reflectance. Non-paddy areas were then classified into corn and bean using time-series NDVI datasets. In the case study result, the proposed classification algorithm showed the best classification performance by selectively classifying crops having similar spectral characteristics, compared with traditional direct supervised classification of time-series NDVI and NIR datasets. Thus, it is expected that the proposed selective hierarchical classification algorithm would be effectively used for producing reliable crop maps.

• Journal of the Korean Chemical Society
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• v.47 no.5
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• pp.447-459
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• 2003

Generalized 2D correlation spectroscopy has been applied extensively to the analysis of spectral data sets obtained during the observation of a system under some external perturbation. It is used in various fields of spectroscopy including IR, Raman, UV, fluorescence, X-ray diffraction, and X-ray absorption spectroscopy (XAS) as well as chromatography. 2D hetero-spectral correlation analysis compares two completely different types of spectra obtained for a system under the same perturbation. Because of the wide range of applications of this technique, it has become one of the standard analytical techniques for the analytical chemistry, physical chemistry, biochemistry, and so on, and for studies of polymers, biomolecules, nanomaterials, etc. In this paper, we will introduce the principle of generalized 2D correlation spectroscopy and its applications that we have studied.

• Food Science of Animal Resources
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• v.28 no.1
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• pp.63-68
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• 2008

To develop the somatic cell counting NIR Spectrum method within a range of 400-2500 nm, eosin-Y, methyl red, methylene blue, resazurin and amido black 10B were tested at 0.01% in raw milk. The PLS (Partial Least Square) results are summarized as follows: Correlation coefficients of the calibration model measurements by NIR spectroscopy in raw milk for eosin-Y, methyl red, methylene blue, resazurin and amido black 10B were 0.78, 0.65, 0.63, 0.65, 0.98 and 0.99, respectively. The correlation coefficients of the prediction model measurements by NIR spectroscopy in raw milk for eosin-Y, methyl red, methylene blue, resazurin and amido black 10B were 0.49, 0.21, 0.36, 0.47, 0.95 and 0.98 respectively. Based on these results, amido black 10B was the best additive for the NIRS somatic cell count method.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.75.1-75.1
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• 2021

MSE (Maunakea Spectroscopic Explorer)는 11.25m 구경의 망원경과 최대 4,000 개의 천체를 한 번에 관측할 수 있는 분광기를 통해 다천체 분광학 연구를 이끌 차세대 관측기기이다. 경희대학교는 망원경에 장착되는 다천체 분광기의 성능 요구사항을 바탕으로 노출 시간 소프트웨어 ETC (Exposure Time Calculator)를 개발하고 있다. ETC는 대기에 의한 연속선 소광, 방출선과 흡수선, 망원경 및 광학 기기의 투과율, 검출기의 암전류와 읽기 잡음을 바탕으로 신호 대 잡음비 S/N (Signal to Noise)을 도출하여 천체를 분광 관측하기 위한 적절한 노출 시간을 계산한다. MSE-ETC는 저분산 LR (Low Resolution, R=3,000), 중분산 MR (Moderate Resolution, R =6,000) 및 고분산 HR (High Resolution, R=40,000)의 관측 모드로 가시광선과 근적외선 영역의 S/N과 파장, 그리고 S/N과 AB등급 간의 상관관계를 보여준다. 본 포스터에서는 개발 중인 MSE-ETC 프로그램의 구조와 작동 알고리즘 및 사용 예를 발표한다.

• Food Science of Animal Resources
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• v.31 no.1
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• pp.115-121
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• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.1
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• pp.31-37
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• 2014

The aim of this study was the non-destructive evaluation of bloody eggs using VIS/NIR spectroscopy. The bloody egg samples used to develop the sorting mode were produced by injecting chicken blood into the edges of egg yolks. Blood amounts of 0.1, 0.7, 0.04, and 0.01 mL were used for the bloody egg samples. The wavelength range for the VIS/NIR spectroscopy was 471 to 1154 nm, and the spectral resolution was 1.5nm. For the measurement system, the position of the light source was set to $30^{\circ}$, and the distance between the light source and samples was set to 100 mm. The minimum exposure time of the light source was set to 30 ms to ensure the fast sorting of bloody eggs and prevent heating damage of the egg samples. Partial least squares-discriminant analysis (PLS-DA) was used for the spectral data obtained from VIS/NIR spectroscopy. The classification accuracies of the sorting models developed with blood samples of 0.1, 0.07, 0.04, and 0.01 mL were 97.9%, 98.9%, 94.8%, and 86.45%, respectively. In this study, a novel nondestructive sorting technique was developed to detect bloody brown eggs using spectral data obtained from VIS/NIR spectroscopy.