• Korean Journal of Optics and Photonics
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• v.18 no.5
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• pp.309-316
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• 2007

We demonstrate the wavelength swept source and signal processing for the frequency domain optical coherence tomography. The laser output performance is improved by using a semiconductor optical amplifier with a booster amplifier. The laser generates 14 mW of average power of which wavelength shift in the lasing spectral shape is compensated. Adopting a Fabry-Perot etalon and digital signal processing, the broadening of the beat frequency due to the variance of wavelength-sweep-velocity is calibrated. The optical coherence tomography system shows 154.4 kHz of axial scanning speed, 0.95mm of depth range, and $12{\pm}0.37{\mu}m$ of axial resolution.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.5
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• pp.643-648
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• 2005

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal grains and forages. If samples could be analyzed without drying and grinding, then sample preparation time and costs may be reduced. This study was conducted to develop robust NIRS equations to predict fermentation quality of corn (Zea mays) silage and to select acceptable sample preparation methods for prediction of fermentation products in corn silage by NIRS. Prior to analysis, samples (n = 112) were either oven-dried and ground (OD), frozen in liquid nitrogen and ground (LN) and intact fresh (IF). Samples were scanned from 400 to 2,500 nm with an NIRS 6,500 monochromator. The samples were divided into calibration and validation sets. The spectral data were regressed on a range of dry matter (DM), pH and short chain organic acids using modified multivariate partial least squares (MPLS) analysis that used first and second order derivatives. All chemical analyses were conducted with fresh samples. From these treatments, calibration equations were developed successfully for concentrations of all constituents except butyric acid. Prediction accuracy, represented by standard error of prediction (SEP) and $R^2_{v}$ (variance accounted for in validation set), was slightly better with the LN treatment ($R^2$ 0.75-0.90) than for OD ($R^2$ 0.43-0.81) or IF ($R^2$ 0.62-0.79) treatments. Fermentation characteristics could be successfully predicted by NIRS analysis either with dry or fresh silage. Although statistical results for the OD and IF treatments were the lower than those of LN treatment, intact fresh (IF) treatment may be acceptable when processing is costly or when possible component alterations are expected.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.208-220
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• 2016

Purpose: Fusel oil is a potent volatile aroma compound found in many alcoholic beverages. At low concentrations, it makes an essential contribution to the flavor and aroma of fermented alcoholic beverages, while at high concentrations, it induced an off-flavor and is thought to cause undesirable side effects. In this work, we introduce Fourier transform near-infrared (FT-NIR) spectroscopy as a rapid and nondestructive technique for the quantitative determination of fusel oil in the Korean alcoholic beverage "soju". Methods: FT-NIR transmittance spectra in the 1000-2500 nm region were collected for 120 soju samples with fusel oil concentrations ranging from 0 to 1400 ppm. The calibration and validation data sets were designed using data from 75 and 45 samples, respectively. The net analyte signal (NAS) was used as a preprocessing method before the application of the partial least-square regression (PLSR) and principal component regression (PCR) methods for predicting fusel oil concentration. A novel variable selection method was adopted to determine the most informative spectral variables to minimize the effect of nonmodeled interferences. Finally, the efficiency of the developed technique was evaluated with two different validation sets. Results: The results revealed that the NAS-PLSR model with selected variables ($R^2_{\upsilon}=0.95$, RMSEV = 100ppm) did not outperform the NAS-PCR model (($R^2_{\upsilon}=0.97$, RMSEV = 7 8.9ppm). In addition, the NAS-PCR shows a better recovery for validation set 2 and a lower relative error for validation set 3 than the NAS-PLSR model. Conclusion: The experimental results indicate that the proposed technique could be an alternative to conventional methods for the quantitative determination of fusel oil in alcoholic beverages and has the potential for use in in-line process control.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.263-272
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• 2020

BACKGROUND: This paper describes the successful discrimination of GM crops from the respective wild type (WT) controls using spectroscopy and chemometric analysis. Despite the many benefits that GM crops, their development has raised concerns, particularly about their potential negative effects on food production and the environment. From this point of view, the introduction of GM crops into the market requires the development of rapid and accurate identification technologies to ensure consumer safety. METHODS AND RESULTS: The development of a GM crop discrimination model using spectroscopy involved the pre-processing of the collected spectral information, the selection of a discriminant model, and the verification of errors. Examples of GM versus WT discrimination using spectroscopy are available for soybeans, tomatoes, corn, sugarcane, soybean oil, canola oil, rice, and wheat. Here, we found that not only discrimination but also cultivar grouping was possible. CONCLUSION: Since for the determination of GM crop there is no pre-defined pre-processing method or calibration model, it is extremely important to select the appropriate ones to increase the accuracy in a case-by-case basis.

• Journal of Preventive Medicine and Public Health
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• v.39 no.2
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• pp.165-170
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• 2006

Objectives : The determination of oxalate in urine is required for the diagnosis and treatment of primary hyperoxaluria, idiopathic stone disease and various intestinal diseases. We examined the possibility of using Fourier transform near-infrared (FT-NIR) spectroscopy analysis to quantitate urinary oxalate. The practical advantages of this method include ease of the sample preparation and operation technique, the absence of sample pre-treatments, rapid determination and noninvasiveness. Methods : The range of oxalate concentration in standard urine solutions was $0-221mg/{\ell}$. These 80 different samples were scanned in the region of 780-1,300 nm with a 0.5 nm data interval by a Spectrum One NTS FT-NIR spectrometer. PCR, PLSR and MLR regression models were used to calculate and evaluate the calibration equation. Results : The PCR and PLSR calibration models were obtained from the spectral data and they are exactly same. The standard error of estimation (SEE) and the % variance were $10.34mg/{\ell}$ and 97.86%, respectively. After full cross validation of this model, the standard error of estimation was $5,287mg/{\ell}$, which was much smaller than that of the pre-validation. Furthermore, the MCC (multiple correlation coefficient) was 0.998, which was compatible with the 0.923 or 0.999 obtained from the previous enzymatic methods. Conclusions : These results showed that FT-NIR spectroscopy can be used for rapid determination of the concentration of oxalate in human urine samples.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.400-407
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• 2008

An Instrument to measure normal spectral emissivity is built using a Fourier Transform-Infrared (FT-IR) spectrometer. The instrument is composed of four main parts, reference blackbody, sample furnace, optics system, and FT-IR spectrometer. Measurement ranges of temperature and wavelength are $200^{\circ}C{\sim}500^{\circ}C$ and $3.5{\mu}m{\sim}20{\mu}m$, respectively. Measured emissivity of the reference blackbody is greater than 0.9993 with combined relative uncertainty less than 0.69%, which can be considered an ideal blackbody. We studied the emissivity of opaque alumina, graphite, anodized aluminum, and steel (IMS 200). It is shown that emissivity increases with the roughness of the steel (IMS 200) surface.

• Journal of the Korean Chemical Society
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• v.30 no.6
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• pp.538-547
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• 1986

The 8 rare earth elements were determined in the monazite concentrates by X-ray fluorescence spectrometry. The spectral line overlapping interferences from the other elements were investigated and the correction methods of interferences were studied using line overlap coefficients. The coefficients were calculated from the ratios of the intensities measured at the diffracted angle (2${\theta}$) of the analytical lines of other elements to the intensity of pure rare earth oxide. The coefficients were used to correct the line overlaps by a regression analysis. The linearities of calibration curves from the corrected intensities were remarkably improved, and their standard deviations were decreased. The analytical results agreed with that of the inductively coupled plasma(ICP) spectrometry within an allowable error range.

• KSBB Journal
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• v.21 no.1 s.96
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• pp.59-67
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• 2006

2D spectrofluorometer produces many spectral data during fermentation processes. The fluorescence spectra are analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). Analysis of the spectral data by PCA results in scores and loadings that are visualized in score-loading plots and used to monitor a few fermentation processes by S. cerevisae and recombinant E. coli. Two chemometric models were established to analyze the correlation between fluorescence spectra and process variables using PCR and PLS, and PLS was found to show slightly better calibration and prediction performance than PCR.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.823-837
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• 2018

The objective of this study was to evaluate the firmness and the sweetness index (SI) of tomatoes with a hyperspectral imaging (HSI) technique within the wavelength range of 1000 - 1550 nm. The hyperspectral images of 95 tomatoes were acquired with a push-broom hyperspectral reflectance imaging system, from which the mean spectra of each tomato were extracted from the regions of interest. The reference firmness and sweetness index of the same sample was measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing methods. The calibration model developed by PLS regression based on the Savitzky-Golay second-derivative preprocessed spectra resulted in a better performance for both the firmness and the SI of the tomatoes compared to models developed by other preprocessing methods. The correlation coefficients ($R_{pred}$) were 0.82, and 0.74 with a standard error of prediction of 0.86 N, and 0.63, respectively. Then, the feature wavelengths were identified using a model-based variable selection method, i.e., variable importance in projection, from the PLS regression analyses. Finally, chemical images were derived by applying the respective regression coefficients on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on the firmness and the SI of the tomatoes. The results show that the proposed HSI technique has potential for rapid and non-destructive evaluation of firmness and the sweetness index of tomatoes.

• Analytical Science and Technology
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• v.16 no.4
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• pp.277-282
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• 2003

The amount of water for the cultivation of citrus is different based on the growing period. The effect of water stress induces to enhance of sugar accumulation in citrus. The water content in the leaves of citrus can be a index for watering during cultivation. The purpose of this study is to determine the water content of citrus leaves non-destructively by using near infrared spectroscopy (NIRS). Citrus leaves were prepared from 'Okitsu' Satusuma mandarin leaves (Citrus unshiu Marc.) ranging from 20.80 to 69.98% of water content by loss on drying method, and NIR reflectance spectra of citrus leaves were acquired by using a fiber optic probe. It was found that the variation of absorbance band 1450 nm from OH vibration of water depending on the water content change. Partial least squares regression (PLSR) was applied to develop a calibration model over the spectral range 1100-1700 nm. The calibration model predicted the water content for the validation set with a standard errors of prediction (SEP) of 0.97%. In order to validate the developed calibration model, routine analyses were performed using independently prepared citrus leaves. The NIR routine analyses showed good results with those of loss on drying method with a SEP of 0.81%. The rapid and non-destructive determination of the water content in citrus leaves was successfully performed by portable NIR system.