• Near Infrared Analysis
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• v.2 no.1
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• pp.29-36
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• 2001

This review paper outlines modern pretreatment methods used in NIR spectroscopy. The pretreatment methods can be divided into four categories. One method in is noise reduction. Smoothing is a representative method for the noise reduction. Another is baseline correction. The second derivative and multiplicative scatter correction (MSC) are most frequently employed for baseline correction. The third is centering and normalization and the last is resolution enhancement. Difference spectra, mean centering and second derivative are used in NIR spectroscopy as resolution enhancement methods. In this paper advantages and drawbacks of pretreatment methods currently used in NIR spectroscopy are discussed with many examples of NIR spectra.

• Journal of Sensor Science and Technology
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• v.26 no.2
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• pp.91-95
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• 2017

Recently, infrared (IR) spectrometers have been required in various fields such as environment, safety, mobile, automotive, and military. This IR dispersive sensor detection method of substances is widely used. In this study, we fabricated a silicon (Si) prism-based near infrared (NIR) spectrometer utilizing micro electro mechanical system (MEMS) technology. Si prism-based NIR spectrometer utilizing MEMS technology consists of upper, middle, and lower substrates. The upper substrate passes through the incident IR ray selectively. The middle substrate, acting as a prism, disperses and separates the incident IR beam. The lower substrate has an amorphous Si (a-Si)-based bolometer array to detect the IR spectrum. The fabricated Si prism-based NIR spectrometer utilizing MEMS technology has the advantage of a simple structure, easy fabrication steps, and a wide NIR region operating range.

• 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.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1072-1072
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• 2001

The purpose of this research is to evaluate rapid determination of phosphorus in soils using NIR spectroscopy. The soil samples from the fields subject to different crops and land-use in Kyeongbook province, Korea were used to make the calibration and validation of the calibration set estimating phosphorus in soil. The NIR reflectance was scanned at 2nm intervals from 1100 to 2500nm with an InfraAlyzer 500 (Bran+Luebbe Co.). Various regression analyses were used to evaluate a NIRS method for determination of phosphorus in the soil. NIR absorption approach requires many soil samples to obtain optimal prediction. Applicability of NIR spectra technique may allow for the analysis of available soil phosphorus rapidly as well as total component within a few seconds.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.7
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• pp.1017-1025
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• 2000

The traditional methods for determining the quality of milk, cheese and meat are tedious and expensive, with a significant wastage of chemicals which pollute the environment. To overcome these disadvantages, the potential of near infrared spectrophotometry (NIR) for monitoring the quality of milk and meat has been evaluated by a number of researchers. While most studies indicate that NIR can be used to predict chemical composition of milk and meat, and to monitor the cutting-point during cheese manufacturing, one study demonstrated the potential of NIR to predict sensory characteristics (e.g. hardness and tenderness) of beef. These calibrations were developed on a small number of samples, limiting their value for adoption by the industries. Now that the sophisticated computer software is available, more robust calibrations need to be developed to monitor both chemical and physical characteristics of meat and meat products simultaneously.

• Near Infrared Analysis
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• v.1 no.2
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• pp.9-20
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• 2000

Recently, near-infrared (NIR) spectroscopy and Raman spectroscopy have received keen interest as powerful techniques for nondestructive analysis of biological materials. The purpose of this review paper is to compare the advantages of NIR and Raman spectroscopy in the nondestructive analysis. Both methods are quite unique and often complementary. For example. NIR spectroscopy is very useful in monitoring in situ the content of components inside biological materials while Raman spectroscopy is very suitable for identifying micro-components on the surface of biological materials. In this article specific characters of the two spectroscopic methods are discussed first and then several examples of applications of NIR and Raman spectroscopy to the biological nondestructive analysis are introduced.

• YAKHAK HOEJI
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• v.46 no.5
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• pp.331-336
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• 2002

The purpose of this study is to develop a non-invasive blood glucose measurement method by a portable near infrared (NIR) system which was newly integrated by our lab. The portable NIR system includes a tungsten halogen lamp, a specialized reflectance fiber optic probe and a photo diode array type InGaAs detector; which was developed by a microchip technology based on the lithography. Reflectance NIR spectra of different parts of human body (finger tip, earlobe, and inner lip) were recorded by using a fiber optic probe. The spectra were collected over the spectral range 1100 ∼ 1740 nm. Partial least squares regression (PLSR) was applied for the calibration and validation for the determination of blood glucose. The calibration model from earlobe spectra presented better results, showing good correlation with a glucose oxidase method which is a mostly used standard method. This model predicted the glucose concentration for validation set with a SEP of 33 mg/dL. This study indicated the feasibility for non-invasive monitoring of blood glucose by a portable near infrared system.

• 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.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1630-1630
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• 2001

NIR specroscopy is widely used today as a quantitative technique for predicting the chemical composition of various agricultural product. However there exist few application for seed quality assessment, especially for seed germinability. This study is to show the possibilities of a nondestructive estimation of germinability in radish (Raphanus sativus L) seeds. The experiment carried out on one radish cultivar (Chung Su Gung Jung, Nong Woo Bio Co., Ltd.) harvested in 1993. NIR(Foss Co.) spectral measurements were carried out on the seeds surface of flat side. The seeds after spectral measurements were planted on blotter individually and observed germination. The seeds were characterized to nongermination and germination group, which in turn grouped to normal and abnormal germination and then compared with the NIR spectra. The spectra from these seed groups were compared each other, The result suggested that NIR spectra could be applicable to determine radish seeds germinability.