• Journal of the Korean Crystal Growth and Crystal Technology
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• v.20 no.1
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• pp.12-20
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• 2010

Metamictization and color change in zircons from Cambodia and Tanzania were investigated. Elements analysis to detect radioactivity of elements such as U and Th, and spectroscopic analysis using UV-VIS and Fourier transform infrared spectroscopy were performed. According to the UV-VIS spectroscopic analysis, it was perceived that many and high intense absorption peaks appeared in blue and colorless zircons, while less and low intense absorption peaks appeared in uranium contained green and yellow zircons. It was found that those stones have made progress to the metamictization. After heat treatment, we could detect opposite results. As the results of FTIR spectroscopy analysis, in the metamict green and yellow zircon, it is showed that 3-phonon combination mode bands of $[SiO_4]^{4-}$ internal vibration in the region of 3100~3400 $cm^{-1}$ are broad and some of them disappear. However, the disappeared bands are observed again due to restored crystal lattice by the heat treatment. Also, $U^{4+}$ peaks that can detect the uranium content in zircon appears at near 4800 $cm^{-1}$ in the green and yellow samples. From this investigation, we could observe the metamictization effect and color change in uranium-bearing zircon by heat treatment using spectroscopic analysis.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3124-3124
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• 2001

The development and evolution of near infra-red spectroscopic (NIS) calibrations for high-moisture materials is an expensive proposition. Such investment is suspect unless the instrument, or instruments, on which calibrations were developed can be preserved intact or re-standardized as component replacements occurs. The objective of this paper is to detail the changes in performance of a six-year old instrument after maintenance in years five and six resulted in collection of spectral data that was increasingly removed from the calibration population. Calibrations for the analysis of mature sugarcane stalks, a high-moisture material, were developed successfully in 1995 using a broad sample population in terms of genetics, and spectral and temporal variation. The spectral library was further broadened in 1996. In 1997, 1999, 1999, and 2000, additional samples constituting 10% of the laboratories throughput were subjected to full component analyses using routine laboratory techniques. These samples were primarily random samples, but were complemented with samples that were significant for the spectral H statistic or for the component t statistic. In 1998, an additional calibration was developed for populations consisting of samples of either mature stalks (culms) or sucker culms. Substantial additional samples numbers were collected for this calibration in 1999 and 2000. Attempts to standardize the scanning spectrophotometer used for these calibrations with a second similar instrument in 1999 failed because the instruments were optically different, and standardization could not account for this. Maintenance adjustments were made to the remote reflectance probe of the original instrument in 1999, and replacement of its PbS detectors was done in 2000. Spectral data collected in 1999 and 2000 yielded spectral populations that were increasingly removed from the respective spectral populations on which the calibrations were developed. The mature stalk calibrations benefited marginally from evolutionary calib.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.7
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• pp.1036-1040
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• 2005

Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean${\pm}$SD) were calculated based on dry matter basis as follows: dry matter: 33.41${\pm}$2.78 (range: 26.41-43.47), protein: 54.04${\pm}$6.63 (range: 36.20-76.09), fat 35.44${\pm}$8.34 (range: 7.50-55.03), calcium 2.55${\pm}$0.65 (range: 0.99-4.41), phosphorus 1.38${\pm}$0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination ($R^2$) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.49.1-49.1
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• 2014

The NISS (Near-infrared Imaging Spectrometer for Star formation history) onboard NEXTSat-1 is the near-infrared instrument onboard NEXTSat-1 which is being developed by KASI. The imaging low-resolution spectroscopic observation in the near-infrared range for nearby galaxies, low background regions, star-forming regions and so on will be performed on orbit. After the System Requirement Review, the optical design is changed from on-axis to the off-axis telescope which has a wide field of view (2 deg. ${\times}$ 2 deg.) as well as the wide wavelength range from 0.95 to $3.8{\mu}m$. The mechanical structure is considered to endure the launching condition as well as the space environment. The design of relay optics is optimized to maintain the uniform optical performance in the required wavelength range. The stray light analysis is being made to evade a light outside a field of view. The dewar is designed to operate the infrared detector at 80K stage. From the thermal analysis, we confirmed that the telescope can be cooled down to around 200K in order to reduce the large amount of thermal noise. Here, we report the current status of the NISS development.

• Bulletin of the Korean Chemical Society
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• v.33 no.12
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• pp.4267-4270
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• 2012

• Analytical Science and Technology
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• v.24 no.6
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• pp.519-526
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• 2011

Chemometrics using near-infrared (NIR) and Raman spectroscopy have found significant uses in a variety quantitative and qualitative analyses of pharmaceutical products in complex matrixes. Most of the pharmaceutical can be measured directly with little or no sample preparation using these spectroscopic methods. During pharmaceutical manufacturing process, analytical techniques with no or less sample preparation are very critical to confirm the quality. This study showed NIR and Raman spectroscopy with principal component analysis (PCA) was very effective for the blending processing control. It is of utmost importance to evaluate critical parameters related to quality of products during pharmaceutical processing. The blending is confirmed by off-line determination of active pharmaceutical ingredient (API) by a conventional method such as high performance liquid chromatography (HPLC) and UV spectroscopy. These analytical methods are time-consuming and ineffective for real time control. This study showed the possibility for the determination of blend uniformity end-point of CR tablets with the use of both NIR and Raman spectroscopy. The samples were acquired from six positions during blending processing with U-type blender from 0 to 30 min. Using both collected NIR and Raman spectral data, principal component analysis (PCA) was used to follow the uniformity of blending and finally determine the end-point. The variation of homogeneity of six samples during blending was clearly found and blend uniformity end-point was successfully confirmed in the domains of principal component (PC) scores.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1251-1251
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• 2001

The routine analysis of milk chemical components is of major importance both for the management of animals in dairy farms and for quality control in dairy industries. NIRS technology is an analytical technique which greatly simplifies this routine. One of the most critical aspects in NIRS analysis of milk is sample preparation and analysis modes which should be fast and straightforward. An important difficulty when obtaining NIR spectra of milk is the high water content (80 to 90%) of this product, since water absorbs most of the infrared radiation, and, therefore, limits the accuracy of calibrating for other constituents. To avoid this problem, the DESIR system was set up. Other ways of radiation-sample interaction adapted for liquids or semi-liquids exist, which are practically instantaneous and with limited or null necessity of sample preparation: Transmission and Folded Transmission or Transflectance. The objective of the present work is to compare the precision and accuracy of milk calibration equations in two analysis modes: Reflectance (dry milk) and Folded Transmission (liquid milk). A FOSS-NIR Systems 6500 I spectrophotometer (400-2500 nm) provided with a spinning module was used. Two NIR spectroscopic methods for milk analysis were compared: a) folded transmission: liquid milk samples in a 0.1 pathlength sample cell (ref. IH-0345) and b) reflectance: dried milk samples in glass fibre filters placed in a standard ring cell. A set of 101 milk samples was used to develop the calibration equations, for the two NIR analysis modes, to predict casein, protein, fat and dry matter contents, and 48 milk samples to predict Somatic Cell Count (SCC). The calibrations obtained for protein, fat and dry matter have an excellent quantitative prediction power, since they present $r^2$ values higher than 0.9. The $r^2$ values are slightly lower for casein and SCC (0.88 and 0.89 respectively), but they still are sufficiently high. The accuracy of casein, protein and SCC equations is not affected by the analysis modes, since their ETVC values are very similar in reflectance and folded transmission (0.19% vs 0.21%; 0.16% vs 0.19% and 55.57% vs 53.11% respectively), Lower SECV values were obtained for the prediction of fat and dry matter with the folded transmission equations (0.14% and 0.25% respectively) compared to the results with the reflectance ones (0.43% and 0.34% respectively). In terms of accuracy and speed of analytical response, NIRS analysis of liquid milk is recommended (folded transmission), since the drying procedure takes 24 hours. However, both analysis modes offer satisfactory results.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.248-252
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• 2001

Near infrared spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. An important merit of the NIRS analytical system is consistent predictions across instruments. However, proper calibration is the most important factor for a NIRS analytical system. Forty samples were obtained from Kyonggi-do Agricultural Research and Extension Services, and used to develop calibrations for crude protein content and crude oil content. Calibrations equations were developed using multiple linear regression (MLR). Accuracy and precision of NIRS predictions were adequate for quality measurement for the two constituents in kidney bean seed. In calibration sample sets (N=30), multiple correlation coefficient between NIR and lab measurements is 0.90 for seed, 0.97 for powder in seed protein concentration and 0.40 for seed and 0.92 for powder in seed oil concentration, respectively. It is concluded that NIRS method is suitable for the determination of seed composition in whole kidney bean.

• Journal of Biosystems Engineering
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• v.41 no.1
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• pp.51-59
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• 2016

Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of $9080-4150cm^{-1}$ (1400-2400 nm) and $1800-970cm^{-1}$, respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and $1^{st}$ and $2^{nd}$ derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.1
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• pp.7-14
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• 1994

This study was conducted to establish the rapid evaluation method of chemical components of rice grain on the basis of non-destructive method. A near-infrared reflectance spectroscopic(NIRS) method was utilized, for the determination of amylose, protein, magnesium, and potassium content of rice. A multiple linear regression analysis for the data obtained by standard laboratory methods and NIRS method was carried out to make a calibration. The standard error of prediction for amylose, protein, magneisum and potassium content were 0.88%, 0.28%, 12.62mg and 10.79mg, respectively. It was concluded that the NlRS method can be useful the rapid determination of amylose, protein, magnesium and potassium content instead of the existing laboratory method.