• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1283-1283
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• 2001

NIR spectroscopy has been used extensively to investigate the structure of water, alcohol and other self-associate molecules because the frequencies of NIR bands due to OH and NH groups strength of hydrogen bonds. We have studied the structure of water -methanol mixtures by use of NIR spectroscopy. Strong features in the 7200-6300 $cm^{-1}$ / region consist of a number of overlapped bands due to the combination of OH antisymmetric and symmetric stretching modes of water and the first overtone of the OH stretching modes of free and hydrogen bonded methanol, while weak fratures in the 6000-5800 cm-1 region are ascribed to the first overtones of $CH_3$ stretching modes of methanol. We will focus the discussion on the $CH_3$ stretching bands. They seem to show a significant shift is not clear from the spectra shown in figure 1(a). Figure 1(b) depicts the second derivative in the 6000-5700 $cm^{-1}$ / region. Now, it is clear from the second derivative that there are two major bands near 5950 and 5900 $cm^{-1}$ / and that they do show a shift be about 30 $cm^{-1}$ / Why do the $CH_3$ bands show the shift with increasing concentration of methanol\ulcorner Probably, the CH, group interacts directly with OH groups of water. The results in figure 1(b) demonstrate the usefulness of the second derivative in resolution enhancement as well as the potential of NIR spectroscopy in the studies of molecular interactions.(Figure omitted).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3121-3121
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• 2001

The factors involved in development of electronic grading systems for commodities such as grains and seeds include determination of the factors that influence the end-product utilization of the commodities, and the degree to which these can be predicted by electronic methods. The possibility of exchanging existing methods of grading by electronic methods has to be considered. The respective merits of techniques such as Digital Imaging and Near-infrared (NIR) spectroscopy have to be considered. Digital Imaging is a computerized version of visual inspection and grading, whereas NIR spectroscopy has the potential for grading on the basis of composition and functionality, Selection and evaluation of NIR instruments is an important factor, as are sampling and sample presentation to electronic instruments, and particularly the engineering involved in sample presentation. Sample assembly, and software for calibration development are described in the presentation. Finally the impact and implications of introduction of electronic grading are discussed with particular attention to marketing of the commodities.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.3
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• pp.314-319
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• 2008

Near infrared (NIR) spectroscopy was used to classify normal and artificially aged nonviable corn (Zea mays L., cv. 'Suwon19') seeds. The spectra at 1100-2500nm were scanned with normal and artificially aged single seeds and analyzed by principle component analysis (PCA). To discriminate normal seeds from artificially aged seeds, a calibration modeling set was developed with a discriminant partial least square 2 (PLS 2) method. The calibration model derived from PLS 2 resulted in 100% classification accuracy of normal and artificially aged (aged) seeds from the raw, the 1st and 2nd derivative spectra. The prediction accuracy of the unknown normal seeds was 88, 100 and 97% from the raw, the $1^{st}$ and $2^{nd}$ derivative spectra, and that of the unknown aged seeds was 100% from all the raw, the $1^{st}$ and $2^{nd}$ derivative spectra, respectively. The results showed a possibility to separate corn seeds into viable and non-viable using NIR spectroscopy.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1122-1122
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• 2001

A compact and handhold near infrared (NIR) system using microspectrometer was developed. This system was suitable not only in the laboratory, but also in the field or in the process. This system was first applied for classification of geographical origin of herbal medicine such as ginseng and sesame. To identify the origin of ginseng on site, the portable NIR system is more suitable for real field application. For this study, using the compact NIR system, soft independent modeling of class analogies (SIMCA) with 1100-1750 nm NIR spectra was utilized for classification of geographical origin (Korea and China) of both ginseng and sesame. The accuracy of results is more than 90%. Quantitative analysis for petroleum such as toluene, benzene, tri-methyl benzene, and ethyl benzene was performed with partial least squares (PLS) regression with NIR 1100-1750 nm spectra. This study showed that the NIR method and gas chromatography (GC), which is a standard method, have good correlations. Furthermore, the ash content of Cornu Cervi Parvum was analyzed and the accuracy was confirmed by the developed compact NIR system.

• Applied Biological Chemistry
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• v.41 no.3
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• pp.240-246
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• 1998

Geographical origin of the Korean, Chinese and Japanese sesame seeds were identified very high accuracy by NIR spectroscopy. The NIR instrument of filter type showed the same accuracy of the monochromator scanning type to identify the geographical origin of the sesame seeds. In case of adulteration between the Korean and Chinese sesame seeds, the ratio of addition could be determined about 10% error level. The reason of identification of geographical origin by NIR spectroscopy, it was supposed to the difference, of oil cake substance.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2002.11a
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• pp.97-117
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• 2002

A chemoinfometrical method for quantitative determination of crystal content of indomethacin (IMC) polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the conventional powder X-ray diffraction method was performed. Pure $\alpha$ and ${\gamma}$ forms of IMC were prepared using published methods. Powder X-ray diffraction profiles and NIR spectra were recorded for six kinds of standard materials with various content of ${\gamma}$ form IMC. The principal component regression (PCR) analyses were performed based on normalized NIR spectra sets of standard samples of known content of IMC ${\gamma}$ form. A calibration equation was determined to minimize the root mean square error of the prediction. The predicted ${\gamma}$ form content values were reproducible and had a relatively small standard deviation. The values of ${\gamma}$ form content predicted by two methods were in close agreement. The results were indicated that NIR spectroscopy provides for an accurate quantitative analysis of crystallinity in polymorphs compared with the results obtained by conventional powder X-ray diffractometry.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1022-1022
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• 2001

To obtain accurate and repeatable analyses using NIR technology it is important to select an NIR instrument and / or its sample presentation attachments which allow the operator to minimize sampling errors without compromising the benefits of NIR analysis -namely rapid, low cost, minimal sample preparation, minimal structural facilities, minimal hazards. For each sample type and consistency there may be different optimal combinations of instrument, sample presentation attachment, and sample preparation. This paper will consider options available to NIR users in the area of plant and soil analysis and evaluate the potential benefits and disadvantages of crop nutrient diagnoses using laboratory based and airborne imaging techniques.

• Journal of electromagnetic engineering and science
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• v.17 no.4
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• pp.186-190
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• 2017

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450-1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.145-148
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• 2015

Young Galactic supernova remnants (SNRs) are where we can observe closely supernova (SN) ejecta and their interaction with the circumstellar/interstellar medium. They also provide an opportunity to explore the explosion and the final stage of the evolution of massive stars. Near-infrared (NIR) emission lines in SNRs mostly originate from shocked dense material. In shocked SN ejecta, forbidden lines from heavy ions are prominent, while in shocked circumstellar/interstellar medium, [Fe II] and $H_2$ lines are prominent. [Fe II] lines are strong in both media, and therefore [Fe II] line images provide a good starting point for the NIR study of SNRs. There are about twenty SNRs detected in [Fe II] lines, some of which have been studied in NIR spectroscopy. We will review the NIR [Fe II] observations of SNRs and introduce our recent NIR spectroscopic study of the young core-collapse SNR Cas A where we detected strong [P II] lines.

• YAKHAK HOEJI
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• v.60 no.2
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• pp.85-91
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• 2016

Drying of granules for tablet formulation is one of the important unit operations. The loss on drying method is traditionally used for this purpose. However, it is a time-consuming method, requiring at least 1 h. Moreover, it is ineffective in monitoring the moisture content of granules during the drying process. In this study, online real-time monitoring of moisture content during the drying process was successfully performed using near-infrared (NIR) spectroscopy. NIR spectra were collected during 15 different drying batches for developing a reliable NIR spectroscopic method. Such a large number of batches were used to develop a more robust partial least squares (PLS) model. NIR spectra collected from 12 batches were used for developing the model that was validated by predicting the moisture content of the samples in the remaining 3 batches. The standard errors of predictions (SEPs) in the measurement of batch 1, batch 2, and batch 3 were 0.52%, 0.57%, and 0.56%, respectively. The online NIR spectroscopic method developed in this study was reliable and accurate in monitoring the moisture content during the drying process.