• 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.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1614-1614
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• 2001

The sweetness (。Bix) of fruit is the main quality factor contributing to the fruit taste. The brix of the apple fruit can be measured non-destructively by near infrared (NIR) spectroscopy, allowing the sweetness grading of individual apple fruit. However, the fruit quality is influenced by various factors such as growing location, producing year, variety and harvest time etc., accordingly the robust NIR calibration is required. In this experimental results are presented the influence of two variations such as growing location and producing year of apple fruit in establishing of calibrations for sweetness, and developed a stable and highly accurate calibration. Apple fruit (Fuji) was collected every year from 1995 to 1997 in 3 different growing locations (Andong, Youngchun and Chungsong) of Kyungpook in Korea. NIR reflectance spectra of apple fruit were scanned in wavelength range of 1100∼2500nm using an InfraAlyzer 500C (Bran+Luebbe) with halogen lamp and PbS detector. The multiple linear regression and stepwise was carried out between the NIR raw spectra and the brix measured by refractometer to select the best regression equations. The calibration models by each growing district were well predicted to dependent sample set, but poorly predicted to independent sample set. Combined calibration model using data of three growing districts predicted reasonable well to a population set drawn from all growing districts(SEP = 0.69%, Bias=-0.075). The calibration models by each harvest year were not transferable across harvest year, however a combined calibration model using data of three harvest years was sufficiently robust to predict each sample sets(SEP = 0.53%, Bias = 0.004).

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.184-193
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• 2014

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of $R{_V}{^2}$, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ${\pm}0.487%$ wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1124-1124
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• 2001

CARNAC is a procedure for obtaining quantitative analysis of a sample by comparison of the NIR spectra of the unknown sample with a database of a large number of samples with NIR spectral and compositional data. The method depends on the compression of the NIR database followed by a modification of the compressed data which emphasizes the required analyte. The method identifies a few very similar samples and the value of the required analyte is calculated from a weighed average of the analyte values for the selected similar samples. The method was originally described at Chambersburg IDRC in 1986 and in the Proceedings of the FT Conference of 1987. This contribution will describe recent work on utilising new methods for both compression and modification.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.39 no.5
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• pp.58-63
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• 2007

This paper sums up all the different steps broached in this project : The NIR spectroscopy technique has been studied and implemented at CTP using a mobile spectrometer device and different optical materials. Methods, based on statistical data analysis (in particular PLS regressions), have been investigated. A laboratory "prototype" using these techniques and methods has been developed in order to control the recovered papers quality, in terms of humidity percentage and sample composition (paper, board, contaminants).

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.220.2-220.2
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• 2003

Many interference in blood should be considered for non-invasive blood glucose level monitoring by near-infrared spectroscopy because blood glucose concentration is about 0.1% (w/v) in normal state. In this study, we investigated the influence of other blood components on blood glucose level monitoring by near-infrared spectroscopy. It carried out by newly developed portable type-NIR system (1100∼2200 nm). Spectrum features of NIR diffuse spectral data were investigated for some blood compnents powder such as hemoglobin, blood serum albumin, urea, uric acid, ascorbate, glucose, cholesterol and as adding glucose powder into other blood components powder mixture. (omitted)

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1526-1526
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• 2001

To improve the accuracy of sweetness sensor in automated sorting operations, it is necessary to clarify unevenness of the sugar content distribution within fruits. And it is expected that the technique to evaluate the content distribution in fruits contribute to the development of the near-infrared (NIR) imaging spectroscopy. Sugiyama (1999) had succeeded to visualize the distribution of the sugar content on the surface of a half-cut green fresh melon. However, this method cannot be applied to red flesh melons because it depends on information of the absorption band of chlorophyll (676 nm), which is affected by the color of the fresh. The objective of this study was to develop the universal visualization method depends on the absorption band of sugar, which can be applied to various kinds of melons and other fruits. The relationship between the sugar contents and absorption spectra of both green and red fresh melons were investigated by using a NIR spectrometer to determine the absorption band of sugar. The combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm was highly correlated with the sugar contents. The wavelength of 902 nm is attributed to the absorption band of sugar. A cooled charge-coupled device (CCD) imaging camera which has 16 bit (65536 steps) A/D resolution was equipped with rotating band-pass filter wheel and used to capture the spectral absorption images of the flesh of a vertically half-cut red fresh melon. The advantage of the high A/D resolution in this research is that each pixel of the CCD is expected to function as a detector of the NIR spectrometer for quantitative analysis. Images at 846 nm, 874 nm, 902 nm and 930 nm were acquired using this CCD camera. Then the 2$\^$nd/ derivative absorbances at 902 nm and 874 nm at each pixel were calculated using these four images. On the other hand, parts of the same melon were extracted for capturing the images and squeezed for the measurement of sugar content. Then the calibration curve between the combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm and sugar content was developed. The calibration method based on NIR spectroscopy techniques was applied to each pixel of the images to convert the 2$\^$nd/ derivative absorbances into the Brix sugar content. Mapping the sugar content value of each pixel with linear color scale, the distribution of the sugar content was visualized. As a result of the visualization, it was quantitatively confirmed that the Brix sugar contents are low at the near of the skin and become higher towards the seeds. This result suggests that the visualization technique by the NIR imaging spectroscopy could become a new useful method fer quality evaluation of melons.

• Analytical Science and Technology
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• v.24 no.2
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• pp.85-93
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• 2011

To protect the steel structure in a high story buildings from fire, the sprayed fire-resistive materials are applied during the construction. Current standard methods to check the quality of sprayed fire-resistive materials are real fire test in lab, which take a long time (several weeks) and expensive. In this study, a simple analytical method to check the quality of sprayed fire-resistive materials is developed using Near Infrared Spectroscopy (NIR). Total 9 kinds of sprayed fire-resisted materials and 3 kinds of normal sprayed material sets were used for the analysis. Each set of materials was 50 to 100 samples. Samples are grinded and make a fine powder. The spectral data acquisition was carried out using FT-NIR spectrometer with a integrating sphere. NIR methods successfully identify the sprayed fire resistive materials by a principle component analysis (PCA) after a vector normalization (SNV) pretreatment.

• Proceedings of the Korean Society for Food Science of Animal Resources Conference
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• 2000.11a
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• pp.1-14
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• 2000

The Near Infrared region of the energy spectrum was first discovered by Hershel in the year 1800. The principles of NIR is based on light absorption of specific organic chemical bonds. The absorption at each wavelength is measured and a spectre is obtained. The spectre is then treated mathematically and with the absorption data is converted to absolute units via a calibration. In the last two decades it has developed dramatically. With the invention of computers and the ability to treat a large amount of data in a very short time the use of NIR for many different purposes has developed very fast. During the last decade with the aid of very powerful PC's the application of NIR technology has become even more widespread. Now or days development of very robust calibrations can be done in a relatively short time with a minimum of resources. The use of Near Infrared Spectroscopy (NIR) in the Meat industry is relatively new. The first installations were taken into operation in the 80ties. The Meat Industry in often referred to as rather conservative and slow to embrace new technologies, they stay with the old and proven methods. The first NIR instruments used by the Meat Industry, and most other industries, were multipurpose build, which means that the sample presentation was not well suited to this particular application, or many other applications for that sake. As the Meat Industry grows and develops to meet the demands of the modern markets, they realise the need for better control of processes and final products. From the early 90 ties and onward the demand for 'rear time' rapid results starts growing, and some suppliers of NIR instruments (and instruments based on other technologies, like X-ray) start to develop and manufacture instrumentation dedicated to the particular needs of the Meat Industry. Today it is estimated that there are approximately 2000 rapid instruments placed in the Meat industry world-wide. By far most of these are used as at-line or laboratory installations, but the trend and need is moving towards real on-line or in-line solutions. NIR is the most cost effective and reproducible analytical procedure available for the twenty first century.