The lunar surface progressively darkens and reddens as a result of sputtering from solar wind particles and bombardment of micrometeoroids. The extent of exposure to these space weathering agents is frequently calculated as the location in a diagram of reflectance at 750 nm vs. 950 nm/750 nm color (R-C). Sim & Kim (2018) examined the R-C trends of pixels within ∼3,500 craters, and revealed that the length (L) and skewness (s) of R-C trends can be employed as a secondary age or maturity indicator. We broaden this research to general lunar surface areas (3,400 tiles of 0.25◦ × 0.25◦ size) in 218 mare basalt units, whose ages have been derived from the size-frequency distribution analysis by Hiesinger et al. (2011). We discover that L and s rise with age until ∼3.2 Gyr and reduce rather rapidly afterward, while the optical maturity, OMAT, reduces monotonically with time. We show that in some situations, when not only OMAT but also L and s are incorporated in the estimation utilizing 750 & 950 nm photometry, the age estimation becomes considerably more reliable. We also observed that OMAT and the lunar cratering chronology function (cumulative number of craters larger than a certain diameter as a function of time) have a relatively linear relationship.

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation and wavelength on the accuracy of the calibration to predict minerals. This study was conducted to assess the effect of sample preparation and wavelength of near infrared spectrum for the improvement of calibration and prediction accuracy of Calcium (Ca) and Phosphorus (P) in imported hay using NIRS. The samples were scanned in reflectance in a monochromator instrument (680–2,500 nm). Calibration models (n = 126) were developed using partial least squares regression (PLS) based on cross-validation. The optimum calibrations were selected based on the highest coefficients of determination in cross validation (R2) and the lowest standard error of cross-validation (SECV). The highest R2 and the lowest SECV were obtained using oven-dry grinded sample preparation and 1,100-2,500 nm wavelength. The calibration (R2) and SECV were 0.99 (SECV: 468.6) for Ca and 0.91 (SECV: 224.7) for P in mg/kg DM on a dry weight, respectively. Results of this experiment showed the possibility of NIRS method to predict mineral (Ca and P) concentration of imported hay in Korea for routine analysis method to evaluate the feed value.

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 -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.

In this study, whole crop rice samples were used to develop near-infrared reflectance (NIR) equations to estimate six forage quality parameters: Moisture, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Ash and relative feed value (RFV). A population of 564 whole crop rice representing a wide range in chemical parameters was used in this study. Undried finely chopped whole crop rice samples were scanned at 1 nm intervals over the wavelength range 680–2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). NIRS calibrations were developed by means of partial least-squares (PLS) regression. The correlation coefficients of cross-validation (R2 cv) and standard error of cross-validation (SECV) for whole crop rice calibration were 0.98 (SECV 1.81%) for moisture, 0.89 (SECV 0.50%) for CP, 0.86 (SECV 1.79%) for NDF, 0.89 (SECV 0.86%) for ash, and 0.84 (SECV 5.21%) for RFV on a dry matter (%), respectively. The NIRS calibration equations developed in this study will be useful in predicting whole crop rice quality for these six quality parameters.

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. The objective of this study was to evaluate the potential of NIRS, applied to imported forage, to estimate the moisture and chemical parameters for imported hays. A population of 392 imported hay representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1 nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R2) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The R2 and SECV for imported hay calibration were 0.92(SECV 0.61%) for moisture, 0.98(SECV 0.65%) for acid detergent fiber, 0.97(SECV 0.40%) for neutral detergent fiber, 0.99(SECV 0.06%) for crude protein and 0.97(SECV 3.04%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of imported hay in Korea for routine analysis method to evaluate the feed value.

극궤도 위성(Aura)에 탑재되어 운용 중인 Ozone Monitoring Instrument (OMI)를 이용하여 동아시아 지역에 대한 등가 람버시안 반사도(Lambertian Equivalent Reflectance; LER)를 유도하였다. 본 연구의 LER 기후값(2004년 10월 -2007년 9월)은 기존 OMI 및 MODIS 결과와 다음 대기환경 변수의 관점에서 비교분석되었다. 파장(자외선, 가시광선), 지표 특성(육지, 해양), 그리고 구름 제거. 자외선 및 가시광선 파장역(328-500 nm)에서 산출된 LER은 최소 반사도뿐만 아니라 세 종류 하위 평균(1, 5, 10% 이내)으로 산출되었다. 이들 중에 10% 평균값이 OMI 결과와 가장 잘 일치하였다. 여기서 상관계수는 0.88, 평균 제곱근 오차는 1.0%. 그리고 평균 편차는 −0.3%이었다. 10% 평균값과 기존 OMI LER값은 해양에서 가시광선에 비하여 자외선 영역에서 큰(~2%) 반면에 육지에서는 작게(~1%) 나타났다. 또한 파장 및 지표 특성에 따른 LER 변동폭은 육지 및 가시광선 조건에서, 특히 만년설 및 사막 지역에서 크게 나타났다(~3%). 최소 반사도값은 해양 및 육지의 표본 지역에서 MODIS에 비하여 약 1.4% 과대 산출되었다. 이러한 원인은 고해상도 MODIS 자료에서의 효과적인 구름 제거에 있다고 분석되었다. MODIS에 대한 10% 평균값의 상대 오차는 기존 OMI 산출물에 비하여 해양에서 작았으나(−0.6%) 육지에서는 컸다(1.5%). OMI 산출물 경우에 육지에서의 작은 상대 오차는 Landsat 자료 이용한 효과적인 구름 제거에 있다고 추정되었다. 본 연구는 정지궤도 환경위성(예, GEMS) 관측을 이용한 지면반사도 산출에 기여할 것으로 기대된다.

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R2) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The R2 and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.

In this study, the effects of powder size and composition on the reflectance of Al-Si based alloys are presented. First, the reflectance of Al-Si bulk and powder are analyzed to confirm the effect of powder size. Results show that the bulk has a higher reflectance than that of powder because the bulk has lower surface defects. In addition, the larger the particle size, the higher is the reflectance because the interparticle space decreases. Second, the effect of composition on the reflectance by the changing composition of Al-Si-Mg is confirmed. Consequently, the reflectance of the alloy decreases with the addition of Si and Mg because dendrite Si and Mg2Si are formed, and these have lower reflectance than pure Al. Finally, the reflectance of the alloy is due to the scattering of free electrons, which is closely related to electrical conductivity. Measurements of the electrical conductivity based on the composition of the Al-Si-Mg alloy confirm the same tendency as the reflectance.

Infrared(IR) heating has many advantages, such as energy efficiency, reduced heating time, cleanliness, equipment compactness, high drying rate and easy automation. These features of IR heating provide widely industrial applications, such as surface heat treatment in semiconductor fabrication, thermoforming of polymers, drying and disinfection of food products, heating to metal forging, and drying of wet materials. In this study, the characteristics of a protected gold mirror were examined by spectrophotometer and the lifetime of the coating layers were evaluated by a cross-cutting method and salt spray test. The effects of manufacturing conditions on the protected gold mirror were seen and remedies for these effects were noted in order to improve the properties of the protected gold mirror in the drying process. The reflectance and lifetime of the protected gold mirror was influenced by manufacturing conditions, such as surface roughness and forming conditions of the anti-oxide layer, the adhesion layer, the reflecting layer and the protection layer. The results of this study showed that the protected gold mirror manufactured using a buffing method for pre-treatment resulted in the most effective reflectance. In addition, Al2O3 coating on an Al substrate as an anti-oxide layer was more effective than the anodizing process in the test of reflectance. Furthermore, the protected gold mirror manufactured by layers forming of various materials resulted in the most effective reflectance and lifetime when coated with Al2O3 as the anti-oxide layer, coated Cr as the adhesion layer, and coated MgF2 as the protection layer.

지면반사도 정보는 열평형 및 환경/기후 모니터링에 중요하다. 본 연구에서는 정지궤도위성의 Geostationary Environment Monitoring Spectrometer (GEMS) 관측에서 300-500 nm 파장 영역의 지면반사도 산출 시에 오차 유발 요 소에 대한 민감도를 조사하였다. 장차 GEMS 지면반사도 산출 시에 오차 분석을 위하여 극궤도 위성의 MODerate resolution Imaging Spectroradiometer (MODIS; 공간 해상도 1 km×1 km) 자료 및 Ozone Mapping Instrument (OMI; 12 km×24 km) 자료 그리고 복사전달모델 수치실험도 분석에 사용하였다. 본 연구에서 오차 유발 요소는 구름, 레일리 산란, 에어로졸, 오존 그리고 지면 특성이다. GEMS 저해상도(8 km×7 km)에서의 구름 탐지율은 MODIS 대비 약 79% 이었으나, GEMS 화소의 운량이 40% 이하에서는 상대적으로 낮았다. 이러한 경향은 구름 이외의 다른 효과(에어로졸, 지면 특성)로 인하여 주로 발생하였다. RGB 영상과 복사전달모델 계산을 기초로 조사된 레일리 산란 효과는 육지에 비하여 해양 지역에서 뚜렷하였다. 지면반사도가 0.2보다 작은 경우에 위성관측 대기상단 반사도는 에어로졸 양에 비례 하였으나, 0.2보다 큰 경우에는 그 반대 경향을 보였다. 또한 에어로졸 양에 의한 지면반사도 산출 오차는 자외선 영역 에서 파장에 따라 급격하게 증가하였으나, 가시광선에서는 일정하거나 다소 감소하였다. 오존 흡수는 자외선 영역(328- 354 nm) 중 328 nm에서 가장 크게 나타났다. 지면반사도가 0.15인 육지 경우에 음의 오존전량 아노말리(-100 DU)로 인한 지면반사도 산출 오차는 +0.1이었다. 본 연구는 GEMS 위성관측을 이용한 지면반사도 원격탐사의 정확도를 높이 는데 기여할 수 있다.

Fe2O3 coated plate mica(Fe2O3/mica) for infrared reflectance red pigment was prepared under hydrothermal treatment. Fe2O3 was perfectly coated on mica via the difference of surface charge between Fe2O3 and mica particles at pH 3. Fe2O3/mica was then calcined at 800 oC to stabilize the coated layer on mica. The infrare (IR) reflectance pigments were characterized by X-ray diffraction, FE-SEM, zeta potential, and a UV-Vis-NIR spectrophotometer. In particular, the CIE color coordinate and IR reflectance properties of Fe2O3/mica pigments were investigated in relation to the thickness variation of the Fe2O3 layer coated on mica of various lateral sizes. The isolation-heat red paints containing the pigments were prepared and optimized with a thinner, settling agent, and dispersant. Then, the films were made. The thermal property of isolation-heat on these films was observed through the relationship of the IR reflectance value, which was based on the variation of the Fe2O3 layer’s thickness coated on mica and mica’s lateral size as IR reflectance pigment. With an increase in IR reflectance on these films, the thermal property of isolation-heat was effectively enhanced.

Nutritive value analysis of feed is very important for the growth of livestock, and ensures the efficiency of feeds as well as economic status. However, general laboratory analyses require considerable time and high cost. Near-infrared reflectance spectroscopy (NIRS) is a spectroscopic technique used to analyze the nutritive values of seeds. It is very effective and less costly than the conventional method. The sample used in this study was a corn kernel and the partial least square regression method was used for evaluating nutrient composition, digestibility, and energy value based on the calibration equation. The evaluation methods employed were the coefficient of determination (R2) and the root mean squared error of prediction (RMSEP). The results showed the moisture content (R2val=0.97, RMSEP=0.109), crude protein content (R2val=0.94, RMSEP=0.212), neutral detergent fiber content (R2val=0.96, RMSEP=0.763), acid detergent fiber content (R2val=0.96, RMSEP=0.142), gross energy (R2val=0.82, RMSEP=23.249), in vitro dry matter digestibility (R2val=0.68, RMSEP=1.69), and metabolizable energy (approximately R2val >0.80). This study confirmed that the nutritive components of corn kernels can be predicted using near-infrared reflectance spectroscopy.

Melamine has been reported to be responsible for kidney stones and renal failure among infants and children. Con-ventional detection methods, High-Performance Liquid Chromatography (HPLC) and Gas Chromatography (GC), aresensitive enough to detect trace amounts of the contaminant, but they are time consuming, expensive, and labor-intensive. Hyperspectral imaging methods, which combine spectroscopy and imaging, can provide rapid and non-destructive means to assess the quality and safety of agricultural products. In this study, near-infrared hyperspectralreflectance imaging combined with partial least square regression analysis was used to predict melamine particleconcentration in dry milk powder. Melamine particles, with concentration levels ranging from 0.02% to 1% byweight ratio (g/g), were mixed with dry milk powder and used for the experiment. Hyperspectral reflectance imagesin the wavelength range from 992.0nm to 1682.1nm were acquired for the mixtures. Then PLSR models weredeveloped with several preprocessing methods. Optimal wavelength bands were selected from 1454.5nm to 1555.6nm using beta-coefficients from the PLSR model. The best PLSR result for predicting melamine concentration inmilk powder was obtained using a 1st order derivative pretreatment with Rv=0.974, SEP=±0.055%, and F=6.

This work was conducted to assess the use of Near-infrared reflectance spectroscopy (NIRS) as a technique to analyze nutritional constituents of Distillers dried grain with solubles (DDGS) and corn quickly and accurately, and to apply an NIRS-based indium gallium arsenide array detector, rather than a NIRS-based scanning system, to collect spectra and induce and analyze calibration equations using equipment which is better suited to field application. As a technique to induce calibration equations, Partial Least Squares (PLS) was used, and for better accuracy, various mathematical transformations were applied. A multivariate outlier detection method was applied to induce calibration equations, and, as a result, the way of structuring a calibration set significantly affected prediction accuracy. The prediction of nutritional constituents of distillers dried grains with solubles resulted in the following: moisture (R2=0.80), crude protein (R2=0.71), crude fat (R2=0.80), crude fiber (R2=0.32), and crude ash (R2=0.72). All constituents except crude fiber showed good results. The prediction of nutritional constituents of corn resulted in the following: moisture (R2=0.79), crude protein (R2=0.61), crude fat (R2=0.79), crude fiber (R2=0.63), and crude ash (R2=0.75). Therefore, all constituents except for crude fat and crude fiber were predicted for their chemical composition of DDGS and corn through Near-infrared reflectance spectroscopy.

For fabricating silicon solar cells with high conversion efficiency, texturing is one of the most effective techniques to increase short circuit current by enhancing light trapping. In this study, four different types of textures, large V-groove, large U-groove, small V-groove, and small U-groove, were prepared by a wet etching process. Silicon substrates with V-grooves were fabricated by an anisotropic etching process using a KOH solution mixed with isopropyl alcohol (IPA), and the size of the V-grooves was controlled by varying the concentration of IPA. The isotropic etching process following anisotropic etching resulted in U-grooves and the isotropic etching time was determined to obtain U-grooves with an opening angle of approximately 60˚. The results indicated that U-grooves had a larger diffuse reflectance than V-grooves and the reflectances of small grooves was slightly higher than those of large grooves depending on the size of the grooves. Then amorphous Si:H thin film solar cells were fabricated on textured substrates to investigate the light trapping effect of textures with different shapes and sizes. Among the textures fabricated in this work, the solar cells on the substrate with small U-grooves had the largest short circuit current, 19.20 mA/cm2. External quantum efficiency data also demonstrated that the small, U-shape textures are more effective for light trapping than large, V-shape textures.