• Journal of Biosystems Engineering
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• v.38 no.3
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• pp.199-207
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• 2013

Purpose: Tomatoes, an important agricultural product in fresh-cut markets, are sometimes a source of foodborne illness, mainly Salmonella spp. Growth cracks on tomatoes can be a pathway for bacteria, so its detection prior to consumption is important for public health. In this study, multispectral Visible/Near-Infrared (NIR) reflectance imaging techniques were used to determine optimal wavebands for the classification of defect tomatoes. Methods: Hyperspectral reflectance images were collected from samples of naturally cracked tomatoes. To classify the resulting images, the selected wavelength bands were subjected to two-band permutations, and a supervised classification method was used. Results: The results showed that two optimal wavelengths, 713.8 nm and 718.6 nm, could be used to identify cracked spots on tomato surfaces with a correct classification rate of 91.1%. The result indicates that multispectral reflectance imaging with optimized wavebands from hyperspectral images is an effective technique for the classification of defective tomatoes. Conclusions: Although it can be susceptible to specular interference, the multispectral reflectance imaging is an appropriate method for commercial applications because it is faster and much less expensive than Near-Infrared or fluorescence imaging techniques.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.2
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• pp.99-103
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• 2015

One-dimensional photonic crystals (1D PCs) were fabricated by RF sputtering technique on p-Si (100), and fused quartz substrates. The 1D PCs structures consisted of $TeO_x$ (x=1.42), and $SiO_2$ with the difference refractive index. In order to estimate the effect on a defect level within 1D PCs structures, samples were prepared with both normal, and defect mode. The structural and optical properties were confirmed by Scanning electron microscope (SEM), and Ultraviolet visible near-infrared spectrophotometer (UV-VIS-NIR) respectively. In the case of a 1D PC normal mode without defect layer, it had a photonic band gap (PBG) in the near infrared (NIR) region. In the case of a 1D PC defect mode with defect layer, it had a sharp transmission band owing to a defect level, and moved towards the longer wavelength after exposing He-Cd laser with a wavelength of 325 nm.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.335-347
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• 2016

The mineralogical and geochemical characteristics of diverse carbonate rocks can be investigated by using VNIRSWIR(visible near infrared-short wavelength infrared) spectroscopic analysis as a rapid, nondestructive, and inexpensive tool. Comparing whole rock analysis to VNIR-SWIR spectroscopic analysis, the analytical method was investigated to estimate CaO contents, mud impurity, and whiteness of carbonate rocks involved in high-grade limestones in the field. We classify typical carbonate rocks in the upper Pungchon Formation in high-grade limestone mine area such as the Gangweon, Chungmu and Baegun mine in the Jeongseon area. The results show that powdered specimen has much higher reflectance than cutted specimen between the same sample. Whiteness is highly correlated with reflectance(0.99) for powdered specimen. The absorption of mineral mixtures shifts in position as a result of the mass ratio of calcite and dolomite in the Chungmu mine by changing to 75:25, 50:50, and 25:75. The absorption peak position in carbonate mixtures is highly correlated with CaO contents(0.98~0.99). Based on color system, the carbonate rocks are grouped into (milky) white, light grey, light brown, grey, and dark grey. The absorption peak position shifts from 2340 nm to 2320 nm as CaO contents decrease from 55.86 wt.% to 29.71 wt.%. We confirmed that absorption peak position shifts depending on the amount of Ca, which is bonded to $CO{_3}^{-2}$, Mg, and Fe contents replacing Ca. This result suggests that CaO contents in carbonate rocks can be considered to quantitative analysis in the field by spectroscopic analysis.

• Applied Science and Convergence Technology
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• v.23 no.5
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• pp.221-239
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• 2014

The global demand for energy has been increasing since past decades. Various technologies have been working to find a suitable alternative for the generation of sustainable energy. Photovoltaic technologies for solar energy conversion represent one of the significant routes for the green and renewable energy production. Despite of remarkable improvement in solar cell technologies, the generation of power is still suffering with lower energy conversion efficiency, high production cost, etc. The major problem in improving the PV efficiency is spectral mismatch between the incident solar spectrum and bandgap of a semiconductor material used in solar cell. Luminescent materials such as rare-earth doped phosphor materials having the quantum efficiency higher than unity can be helpful for photovoltaic applications. Quantum cutting phosphors are the most suitable candidates for the generation of two or more low-energy photons for the absorption of every incident high-energy photons. The phosphors which are capable of converting UV photon to visible and near-IR (NIR) photon are studied primarily for photovoltaic applications. In this review, we will survey various near IR quantum cutting phosphors with respective to their synthesis method, energy transfer mechanism, nature of activator, sensitizer and dopant materials incorporation and energy conversion efficiency considering their applications in photovoltaics.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1512-1512
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• 2001

The University of Cordoba conducts since 1991 a breeding program to obtain new olive cultivars from intraspecific crosses. The objective is to obtain new early bearing and high-quality cultivars. In plant breeding, many seedlings must be tested to increased the chance of getting desirable genotypes. Therefore, fast, cheap and accurate methods of analysis are necessary. The conventional laboratory techniques are costly and time-consuming. Near Infrared Spectroscopy (NIRS) can satisfy the characteristics requested by plant breeders and offers many advantages such as the simultaneous analysis of many traits and cheap cost. The objective of this work was to asses the performance of NIRS to estimate oil fruit components (fruit weight, flesh moisture, flesh/stone ratio and oil flesh content in dry weight basis) and fatty acid composition in olive fruit. Genotypes from reciprocal crosses between ‘Arbequina’, ‘Frantoio’ and ‘Picual’ cultivars have been used in this study. A total of 287 samples, each from a single plant, were scanned using a DA-7000 Diode Array VIS/NIR Analysis System (Perten Instruments), which covers the visible and NIR range from 400-1700 nm. All samples were analysed for fatty acid composition (gas chromatography) and 220 for oil fruit components (oil content by nuclear magnetic resonance), 70% and 30% of samples were randomly assign for the calibration and validation sets respectively. The preliminary results shows that calibration for palmitic, oleic and linoleic acids were highly accurate with calibration and validation values of $r^2$ from 0.85 to 0.95 and 0.76 to 0.91 respectively. Calibration for palmitoleic and estearic acids were less accurate, probably because of the narrow range of variability available for these fatty acids. For the oil fruit components, calibration were high accurate for flesh moisture and oil flesh content in dry weight basis ($r^2$ higher than 0.90 in both calibration and validation sets) and less accurate for the other characteristics evaluated. The first results obtained indicate that NIRS analysis could be an ideal technique to reduce the cost, time and chemical wasted necessary to evaluate a large number of genotypes and it is accurate enough to use for pre-selecting genotypes in a breeding program.

• 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.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.156-158
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• 2007

The radiance observed from the ocean depends on the illumination and viewing geometry along with the water properties, and this variation is called the bidirectional effect which is important to be considered in ocean color remote sensing. In the present study, as a preliminary step, the spectral-angular radiances in coastal water were investigated with experiments for a range of viewing geometric conditions $(0-70^{\circ})$. Over a phytoplankton-dominated water surface the upward radiance for visible and near-infrared wavelengths (example, SeaWiFS and GOCI) increased at nadir and decreased toward the near-horizon, becoming dependent of viewing angles (with higher radiance at nadir view angle and lower radiance at near-horizon viewing angle). This variations were better expressed by the Q-factor, which relates upwelling radiance to the upwelling irradiance (i.e., $Q=E_u/L_u$, also dependent on Sun's position). The Q-factor for this case was more non-uniform with the considered wavelengths and was dependent on viewing geometric conditions. These experimental results confirm the previous similar findings in other coastal waters.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.337-351
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• 2004

Our laboratory originally developed the compact, multi-spectral, automatic aerial photographic system PKNU3 to allow greater flexibility in geological and environmental data collection. We are currently developing the PKNU3 system, which consists of a color-infrared spectral camera capable of simultaneous photography in the visible and near-infrared bands; a thermal infrared camera; two computers, each with an 80-gigabyte memory capacity for storing images; an MPEG board that can compress and transfer data to the computers in real-time; and the capability of using a helicopter platform. Before actual aerial photographic testing of the PKNU3, we experimented with each sensor. We analyzed the lens distortion, the sensitivity of the CCD in each band, and the thermal response of the thermal infrared sensor before the aerial photographing. As of September 2004, the PKNU3 development schedule has reached the second phase of testing. As the result of two aerial photographic tests, R, G, B and IR images were taken simultaneously; and images with an overlap rate of 70% using the automatic 1-s interval data recording time could be obtained by PKNU3. Further study is warranted to enhance the system with the addition of gyroscopic and IMU units. We evaluated the PKNU 3 system as a method of environmental remote sensing by comparing each chlorophyll image derived from PKNU 3 photographs. This appraisement was backed up with existing study that resulted in a modest improvement in the linear fit between the measures of chlorophyll and the RVI, NDVI and SAVI images stem from photographs taken by Duncantech MS 3100 which has same spectral configuration with MS 4000 used in PKNU3 system.

• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.243-249
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• 2019

The purpose of this study is to analyze the reflectance of bed materials according to changes in the water level using a drone-based hyperspectral sensor. For this purpose, we took hyperspectral images of bed materials such as soil, gravel, cobble, reed, and vegetation to compare and analyze the spectral data of each material. To adjust the water level, we constructed an experimental channel to control the discharge and installed the bed materials within the channel. In this study, we configured 3 cases according to the water level (0.0 m, 0.3 m, 0.6 m). After the imaging process, we used the mean value of 10 points for each bed material as analytical data. According to the analysis, each material showed a similar reflectance by wavelength and the intrinsic reflectance characteristics of each material were shown in the visible and near-infrared region. Also, the deeper the water level, the lower the peak reflectance in the visible and near-infrared region, and the rate of decrease differed depending on the bed material. We expect the intrinsic properties of these bed materials to be used as basic research data to evaluate river environments in the future.