• 한국초지조사료학회지
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• 제24권1호
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• pp.81-90
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• 2004

Farmers need timely information on the nutritional status of their animals and the nutritive value of pastures and supplementary feeds if they are to apply successfully this existing nutritional information. Near infrared reflectance(NIR) spectroscopy has been used over the last forty years to analyse accurately protein, fiber, and other organic components in animal foods. NIR spectroscopy is a rapid, non-destructive, and non-polluting technology. When properly calibrated, NIR spectroscopy is used successfully with both concentrate and forage feeds. NIR methods predict in vitro digestibility accurately and precisely, and can predict in vivo digestibility at least as well as conventional "wet chemistry" methods such as in vivo digestion or the pepsin-cellulase method, and much more rapidly. NIR technology has been applied to the routine monitoring (through analysis of feces samples) of the nutritional status of cattle and other grazing animals. This report reviews the use of near infrared reflectance(NIR) spectroscopy to monitor the nutritive value of animal feeds and the nutritional status of grazing animals.

• 한국분말재료학회지
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• 제28권1호
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• pp.38-43
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• 2021

A high NIR-reflective black pigment is developed by Mn doping of Fe2O3. The pigment powders are prepared by spray pyrolysis, and the effect of the Mn concentration on the blackness and optical properties is investigated. Mn doping into the crystal lattice of α-Fe2O3 is found to effectively change the powder color from red to black, lowering the NIR reflectance compared to that of pure Fe2O3. The pigment doped with 10% Mn, i.e., Fe1.8Mn0.2O3, exhibits a black color with an optical bandgap of 1.3 eV and a Chroma value of 1.14. The NIR reflectance of the prepared Fe1.8Mn0.2O3 black pigment is 2.2 times higher than that of commercially available carbon black, and this material is proven to effectively work as a cool pigment in a temperature rise experiment under near-infrared illumination.

• 한국농공학회논문집
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• 제51권3호
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• pp.37-43
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• 2009

The objective of this study was to investigate the basic relationships between spectral reflectance and varying concentrations of sediment in surface waters. An experimental method for determining suspended sediment concentration (SSC) in the water by use of a spectroradiometer above the water surface, in visible and near-infrared (NIR) wavelengths, is applied. The main advantage of the method is the direct comparison of spectral reflectance and the SSC, but it requires an accurate knowledge of the water body and sediment. Therefore numerous spectroradiometric measurements are carried out in situ measurements, for SSC, ranging from zero to 100 percentage and two types of sediment applied in the water tank. The results indicate that the suspended sediment causes increasing spectral reflectance response in waters. We observed that spectral reflectance increases with SSC, first at the lower wavelengths (430-480 nm), then in the middle wavelengths (570-700 nm), and finally, in the NIR domain (800-820 nm); a characteristic maximum reflectance appears at 400-670 nm. Relationships between the wavelength, integral value, and the SSC were evaluated on the basis of the regression analysis. The regression curve for the relation between the wavelength, integral value, and the SSC were determined ($R^2$>0.98). Finally, the specular wavelength can be estimated to recognize the sediment and to improve SC estimation accuracy in the water.

• 폴리머
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• 제24권1호
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• pp.65-71
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• 2000

산무수물 경화 에폭시 수지의 잠재 특성 및 경화 동력학을 근적외선 분광분석법을 통해서 논의하였다. 잠재 특성과 경화 거동의 확인은 각기 다른 온도에서 에폭사이드와 수산기의 NIR reflectance를 측정함으로써 행해졌으며 반응 과정에서 4000~7100$cm^{-1}$ / 스펙트럼 범위의 주된 NIR 흡수피크의 기점, 위치 그리고 전이에 대한 포괄적인 분석이 이루어졌다. 반응의 정도는 에폭사이드의 함량과 경화 온도에 의존적인 4530$cm^{-1}$ /의 NIR 흡수 피크로부터 결정하였다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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• pp.521-524
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• 2000

Nearinfra-red(NIR) reflectance NIR a spectra (400 to 2,100 nm) were collected on 32 beef samples to find feasibility of predicting beef tenderness. The study to predict beef tenderness was accomplished with the stepwise second differential data of the collected NIR spectra. Beef tenderness was measured by Warner-Bratzler(WB) shear force using a Universal Testing Machine(UTM). After modeling the relation between Warner-Bratzler shear force and NIR spectrum of 19 samples among the 32 beef samples, the verification was carried out through predicting the other 13 samples. The SEC and R$^2$ values in the prediction equation were 9.07(N) and 0.6463, respectively. The SEP and R$^2$ were 14.8(N) and 0.7082 (wave length 552 nm, 1988 nm) respectively. The result implied that it was possible to predict the beef tenderness using NIR spectrum and that the tenderness could be predicted non-destructively in real time.

• Agricultural and Biosystems Engineering
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• 제6권1호
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• pp.15-21
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• 2005

This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

• Journal of Biosystems Engineering
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• 제26권5호
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• pp.475-480
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• 2001

Sensing soil organic matter is crucial for precision farming and environment friendly agriculture. Near infra-red(NIR) was utilized to measure the soil organic matter. Multivariate calibration methods, including stepwise multiple linear regression(MLR), principal components recession(PCR) and partial least squares regression(PLS), were applied to soil spectral reflectance data to predict the organic matter content. The effect of soil particle size and water content was studied. The range of soil organic matter contents was from 0.5 to 11%. Near infrared (NIR) region from 700 to 2,500nm was applied. For uniform soil particle size, result had good correlation (R$\^$2/ = 0.984, standard error of prediction= 0.596). The effect of soil particle size could be eliminated with 1st order derivative of the NIR signal. However. moist soil had a little lower correlation. R$\^$2/ was 0.95 and standard error of prediction was 0.94% using the PLS method. The results showed the possibility of soil organic matter measurement using NIR reflectance on the field.

• 약학회지
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• 제46권5호
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• pp.331-336
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• 2002

The purpose of this study is to develop a non-invasive blood glucose measurement method by a portable near infrared (NIR) system which was newly integrated by our lab. The portable NIR system includes a tungsten halogen lamp, a specialized reflectance fiber optic probe and a photo diode array type InGaAs detector; which was developed by a microchip technology based on the lithography. Reflectance NIR spectra of different parts of human body (finger tip, earlobe, and inner lip) were recorded by using a fiber optic probe. The spectra were collected over the spectral range 1100 ∼ 1740 nm. Partial least squares regression (PLSR) was applied for the calibration and validation for the determination of blood glucose. The calibration model from earlobe spectra presented better results, showing good correlation with a glucose oxidase method which is a mostly used standard method. This model predicted the glucose concentration for validation set with a SEP of 33 mg/dL. This study indicated the feasibility for non-invasive monitoring of blood glucose by a portable near infrared system.

• 농업과학연구
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• 제40권2호
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• pp.163-167
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• 2013

Objective of the study was to compare reflectance spectrum in the blade and the vein parts of cabbage and kale leaves. A total 6 cabbage and kale leaves were taken from a plant factory in Chungnam National University, Korea. Spectra data were collected with a UV/VIS/NIR spectrometer (model: USB2000, Ocean Optics, FL, USA) in the wavelength region of 190 - 1130 nm. Median filter smoothing method was selected to preprocess the obtained spectra data. We computed reflectance difference by subtraction of averaged spectrum from individual spectrum. To estimate correlation at different parts of cabbage and kale leaves, cross - correlation method was used. Differences between cabbage and kale leaves are clearly manifested in the green, red and near - infrared ranges. The percent reflectance of cabbage leaves in the NIR wavelength band was higher than that of kale leaves. Reflectance in the blade part was higher than in the vein part by 18%. Reflectance difference in the different parts of cabbage and kale leaves were clear in all of the wavelength bands. Standard deviation of reflectance difference in the vein part was greater for kale, while the value in the blade part was greater for cabbage leaves. Standard deviation of cross - correlation increased from 0.092 in the first sensor (UV/VIS) and 0.007 in the second sensor (NIR) to 0.099 and 0.015, respectively.

• Journal of Biosystems Engineering
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• 제23권3호
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• pp.253-258
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• 1998

The part I was for developing regression models to predict the moisture content, protein content and viscosity of brown and milled rice using Near Infrared(NIR) Reflectance analyzer. The purpose of this study(part II) is to measure fundamental data required for the prediction of rice quality, and to develop regression models to predict the protein content of brown and milled rice, brown rice yield from undried paddy powder by using Near Infrared(NIR) Reflectance analyzer. The results of this study were summarized as follows : The predicted values of protein contents obtained from the undried paddy powder were well correlated to the measured values from brown and milled rice. The predicted yields of brown rice from undried paddy powder were not well correlated to the lab measured values from dried paddy. Continuous study in wavelength selection and of constituent relationship is necessary for practical application.