• Archives of Pharmacal Research
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• v.28 no.4
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• pp.458-462
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• 2005

The water content of skin was determined using a FT near infrared (NIR) spectrometer. NIR diffuse reflectance spectra were collected from hairless mouse, in vitro, and from human inner arm, in vivo. It was found that the variation of NIR absorbance band 1450 nm from OH vibration of water and 1940 nm from the combination involving OH stretching and OH deformation, depending on the absolute water content of separated hairless mouse skin, in vitro, using the FT NIR spectrometer. Partial least squares regression (PLSR) was applied to develop a calibration model. The PLS model showed good correlation. For practical use of the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo on the basis of the relative water content of stratum corneum from the conventional capacitance method. The PLS model predicted human skin moisture with a standard errors of prediction (SEP) of 3.98 at 1130-1830 nm range. These studies showed the possibility of a rapid and nondestructive skin moisture measurement using FT NIR spectrometer.

• YAKHAK HOEJI
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• v.48 no.3
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• pp.171-176
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• 2004

This study was described for measuring clinically relevant levels of glucose in undiluted plasma and whole blood by near-infrared (NIR) spectroscopy. Result from an initial measurement of major blood components powder was over-lapped the absorption bands of glucose at 1500-1600 nm. However, the NIR data of blood components were clearly separated by principle component analysis (PCA) space. By the use of partial least squares (PLS) regression, glucose concentrations in undiluted plasma and whole blood could be determined with standard errors of prediction (SEP) of 15 mg/dl and 76 mg/dl, respectively. Although these blood components possessed strong absorption bands that overlapped with the absorption bands of glucose, successful calibration models could be carried out.

• YAKHAK HOEJI
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• v.48 no.3
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• pp.177-181
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• 2004

Non-invasive blood glucose measurement from mouse tail was performed by near-infrared (NIR) spectroscopy. Three groups; normal, type I diabetes (insulin dependent diabetes mellitus, IDDM), type II diabetes (non-insulin dependent diabetes mellitus, NIDDM) group, were studied over a 10 weeks period with the collection of near-infrared (NIR) spectra. Spectral variations from long-term measurement (10 weeks) from dramatic and nonlinear changes in the optical properties of the live tissue sample were compensated by chemometrics techniques such as principle component analysis (PCA) and partial least squares (PLS) regression. The effect from mouse body temperature changes on NIR spectral data was also considered. This study showed that the compensation of variations from long-term measurement and temperature changes improved calibration accuracy of non-invasive blood glucose measurement.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.218.3-218.3
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• 2003

In this study, a FT-NIR spectroscopy was used to determine skin moisture. NIR diffuse reflectance spectra were collected from separated dorsal and abdominal hairless mouse skin. Partial least squares regression (PLSR) was applied to develop calibration models that determine the water content. The seven spectra regions, such as 833-2500, 1100-2250, 1100-1750, 1750-2250, 1200-1600, 1800-2200, and 1200-2200 except 1600-1800 nm, were investigated for the best model by PLSR. The developed model predicted skin moisture for validation set with a standard errors of prediction (SEP) of 4.43%, when used 833-2500 nm. (omitted)

• Analytical Science and Technology
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• v.37 no.1
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• pp.12-24
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• 2024

In this study, laser-induced breakdown spectroscopy (LIBS) was used to estimate the degree of rice polishing. As-threshed rice seeds were dehusked and polished for different times, and the resulting grains were analyzed using LIBS. Various atomic, ionic, and molecular emissions were identified in the LIBS spectra. Their correlation with the amount of polished-off matter was investigated. Na I and Rb I emission line intensities showed linear sensitivity in the widest range of polished-off-matter amount. Thus, univariate models based on those lines were developed to predict the weight percent of polished-off matter and showed 3-5 % accuracy performances. Partial least squares-regression (PLS-R) was also applied to develop a multivariate model using Si I, Mg I, Ca I, Na I, K I, and Rb I emission lines. It outperformed the univariate models in prediction accuracy (2 %). Our results suggest that LIBS can be a reliable tool for authenticating the degree of rice polishing, which is closed related to nutrition, shelf life, appearance, and commercial value of rice products.

• Analytical Science and Technology
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• v.12 no.5
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• pp.375-381
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• 1999

Near infrared spectrophotometry(NIR) was developed as a non-invasive determination of blood alcohol. The first pure alcohol/water samples were prepared with ethanol concentration from 0.01 to 0.1%(w/w). Analysis of the second-derivative data was accomplished with multilinear regression(MLR). The standard error of calibration(SEC) of ethanol in ethanol/water solutions was approximately 0.0039%. The calibration models were established from the blood alcohol spectra by MLR and PLSR analysis. The best calibration was built with the second-derivative spectra of 2266 and 2326 nm by MLR. Second-derivative spectra in the spectral ranges of 1100~1340, 1500~1796 and 2064~2300 nm with four PLSR factors provided the standard error of prediction(SEP) of 0.030%(w/w). These results indicate that NIR may be applied for a fast non-invasive determination of alcohol in the blood.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.2
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• pp.106-111
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• 2001

The applicability of near infrared reflectance spectroscopy(NIRS) was tested to determine the protein and oil contents in ground soybean [Glycine max (L.) Merr.] seeds. A total of 189 soybean calibration samples and 103 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing and 1 point second smoothing) math treatment condition with SNV-D (Standard Normal Variate and Detrend) scatter correction method and entire spectrum by using MPLS (Modified Partial Least Squares) regression. In the case of oil, the best equation was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared (1100-2500nm) region by using MPLS regression. Validation of these NIRS equations showed very low bias (protein:-0.016%, oil : -0.011 %) and standard error of prediction (SEP, protein: 0.437%, oil: 0.377%) and very high coefficient of determination ($R^2$, protein: 0.985, oil : 0.965). Therefore, these NIRS equation seems reliable for determining the protein and oil content, and NIRS method could be used as a mass screening method of soybean seed.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.4
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• pp.580-583
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• 2005

We have evaluated the application of spectroscopy using an insertion-type fiber-optic probe and a sensor at wavelengths from 400 to 1,100 nm to the measurement of milk fat content on dairy farms. The internal reflectance ratios of 183 milk samples were determined with a fiber-optic spectrophotometer at 5$^{\circ}C$, 20$^{\circ}C$ and 40$^{\circ}C$. Partial least squares (PLS) regression was used to develop calibration models for the milk fat. The best accuracy of determination was found for an equation that was obtained using smoothed internal reflectance data and three PLS factors at 20$^{\circ}C$. The correlation coefficients between predicted and reference milk fat at 5$^{\circ}C$, 20$^{\circ}C$ and 40$^{\circ}C$ were r=0.753, r=0.796 and r=0.783, respectively. The predictive explained variances ($Q^2$) of the final model, moreover, were more than 0.550 at all temperatures, and the regression coefficients of determination ($R^2$) were more than 0.6 (60%). Our results indicate that milk has different internal reflectance measured in the range of visible and near infrared wavelengths (400 to 1,100 nm), depending on its fat content.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.681-692
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• 2018

This study was performed to select the significant wavelengths for predicting the chlorophyll content of grafted cucumber seedlings using hyperspectral images. The visible and near-infrared (VNIR) images and the short-wave infrared images of cucumber cotyledon samples were measured by two hyperspectral cameras. A correlation coefficient spectrum (CCS), a stepwise multiple linear regression (SMLR), and partial least squares (PLS) regression were used to determine significant wavelengths. Some wavelengths at 501, 505, 510, 543, 548, 619, 718, 723, and 727 nm were selected by CCS, SMLR, and PLS as significant wavelengths for estimating chlorophyll content. The results from the calibration models built by SMLR and PLS showed fair relationship between measured and predicted chlorophyll concentration. It was concluded that the hyperspectral imaging technique in the VNIR region is suggested effective for estimating the chlorophyll content of grafted cucumber leaves, non-destructively.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.335-340
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• 2004

This study was conducted to evaluate the internal quality of Korean red ginseng using VIS/NIR transmittance spectra. To classify the internal qualities, partial least squares(PLS) regression was conducted. The main results are as follows: To develop the PLS model, several wave bands were divided and incorporated into the model. Among the bands, the wavelength range of 550-1,020nm, excluded noise signal, showed the best evaluation results. Effect of step size on the performance of quality evaluation showed optimal at 15 steps. In order to enhance the accuracy of quality evaluation, the abnormal spectrum shape was considered first and then the PLS model was applied. Among the 150 samples, 12 samples were evaluated by the spectrum shape. In this study, to develop the optimal PLS regression model, among the 150 samples, 138 samples was used with exception of 12 samples which could evaluate the spectrum shape. The result of quality evaluation was promising as SEC and correlation coefficient were 1.09 and 0.967, respectively, and SEP and correlation coefficient were 1.04 and 0.958, respectively.