• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.5
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• pp.359-365
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• 2004

To study the lipid adsorption characteristic of chitosans with different molecular weights and the degrees of deacetylation, in vitro test and near-infrared (NIR) spectroscopic analysis have been performed for the measurement of lipid adsorption characteristics of chitosan. The degrees of deacetylation in chitosans were $70{\%},\;85{\%}\;and\;92{\%}$ at different deacetylation times (1 hr, 2 hrs, 3 hrs), respectively. The molecular weight of each chitosan was controlled by enzymatic hydrolysis, and then the molecular weight of the chitosan was 4 kDa. The bulk density, water holding capacity and fat binding capacity of each chitosan powder were $96.2-504.0{\%},\;374.4-1217.9{\%},\;and\;307.0-659.3{\%}$, respectively. The higher molecular weight of chitosan was exhibited the lower bulk density and the higher water and fat binding capacities. Bindinf capacities of chitosan powders to bile salts, cholesterol and linoleic acid were $41.2-63.3{\%},\;40.8-67.4{\%},\;42.6-72.6{\%}$, respectively. In NIR spectrum of lipid adsorbed chitosan the occurrence static eletronical binding between chitosan and lipid was identified by NIR spectrum peak induced from combination of carboxylic group in lipid and amino group in chitosan. In conclusion, the higher degree of deacetylation and molecular weight of chitosan showed the higher lipid binding capacity and the lipid adsorption of chitosan were occurred by combination of carboxylic group in lipids and amino group in chitosan.

• 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.

• Journal of Sensor Science and Technology
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• v.11 no.2
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• pp.93-101
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• 2002

The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. Today, nondestructive methods are widely researched. The quality and the grade of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by infernal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit's color image and make chain code faster than conventional method. The chain code helps compute a size of fruit image and find multiple loading of a fruit in single cup or fruit between two cups. The designed classification system sorts a citrus at speed of 8 fruit/s, with evaluating a brix, an acidity and a size grade.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.165-168
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• 2006

Fourier transform-near infrared spectroscopy (FT-NIRS) was evaluated for determination of total dietary fiber (TDF) content of brown rice. Enzymatic-gravimetric method was suitable to obtain reference values for calibration of NIR at 1,000-2,500 nm range. Standard error of laboratory procedure ranged 0.17 to 0.72%. Partial least square (PLS) regression was used to develop the calibration equations. Regression was performed automatically using NIRCal chemometric software. Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP), showing 0.9780, 0.0636, and 0.0642, respectively. This prediction model can be used for determination of TDF in brown rice and would be useful for real-time analysis in food industry.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.356-360
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• 2002

The honey samples harvested in 1996, 1997, and 1998 were used for calibration and validation. NIR spectra were obtained using NIR spectrometer and quartz glass device with gold coating diffuser. Multiple linear regression and partial least square were used for calibrations. The correlation coefficient (RSQ) and standard error of prediction (SEP) obtained for moisture were 0.997 and 0.1%, respectively. The RSQ and SEP for fructose and glucose were 0.926 and 0.951%, and the SEP were 0.54% and 0.52% respectively. The validation results for sucrose, maltose, HMF definition, and acidity of honey were considered to be sufficient for practical use RSQ and SEP for SCIR were 0.950 and $1.08%_{\circ}$, respectively. These results are indications of the rapid determination of purity of the honey through NIR analysis.

• Journal of the Korean Wood Science and Technology
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• v.45 no.2
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• pp.202-212
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• 2017

This study was to establish the interrelation between chemical compositions and near infrared (NIR) spectra for the classification on distinguishability of domestic gymnosperms. Traditional wet chemistry methods and infrared spectral analyses were performed. In chemical compositions of five softwood species including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cypress (Chamaecyparis obtusa), and cedar (Cryptomeria japonica), their extractives and lignin contents provided the major information for distinction between the wood species. However, depending on the production region and purchasing time of woods, chemical compositions were different even though in same species. Especially, red pine harvested from Naju showed the highest extractive content about 16.3%, whereas that from Donghae showed about 5.0%. These results were expected due to different environmental conditions such as sunshine amount, nutrients and moisture contents, and these phenomena were also observed in other species. As a result of the principal component analysis (PCA) using NIR between five species (total 19 samples), the samples were divided into three groups in the score plot based on principal component (PC) 1 and principal component (PC) 2; group 1) red pine and Korean pine, group 2) larch, and group 3) cypress and cedar. Based on the chemical composition results, it was concluded that extractive content was highly relevant to wood classification by NIR analysis.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1527-1527
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• 2001

Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.

• Analytical Science and Technology
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• v.30 no.5
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• pp.234-239
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• 2017

Identifying the components of residues that are not completely burned at the sites of fires site can provide valuable information for tracing the causes of fires. In order to clarify the types of plastic combustion residues found at the scenes of fires, we studied the residue formed after the combustion of polyethylene (PE) and acrylonitrile butadiene styrene (ABS). Plastic samples were burned at 200, 300, 350, 400, and $500^{\circ}C$ for 3 min using a cone calorimeter, and the changes in weight and combustion products were observed. The powder products obtained by lyophilization and pulverization of the combustion products obtained at each temperature were analyzed by a Fourier transform-near infrared (FT-NIR) spectrometer. When the PE samples were burned, the weight did not change up to $350^{\circ}C$, however a significant change in the weight could be measured above $400^{\circ}C$. The principal component analysis (PCA) of the FT-NIR spectra of the PE and ABS samples obtained at each temperature confirmed that the combustion residues at each temperature were PE and ABS, respectively. Therefore, the types of unburned plastics found at the sites of fires can be confirmed rapidly by near infrared spectroscopy.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.4
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• pp.321-326
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• 2002

Near infrared spectroscopy (NIR), is recently applied to analysis of food, and it gives non-destructive and highly reproducible results. The objectives of this study were to assay protein, lipid and starch content in Alaska pollack surimi and to investigate application in seafood. NIR spectra showed the absorbance signal at 1,510 nm, 2,050 nm, 2,170 nm and 2,180 nm for protein, and signal were increased with protein content. Standard error of equation (SEE) was 0,296 and standard error of prediction (SEP) was 0.327. In analysis of lipid in Alaska pollack surimi by NIR, near infrared spectra of lyophilized Alaska pollack surimi were scanned and the signals of absorbance from C-H functional groups in lipid were identified at 1,730 nm, 1,740 nm and 2,300 nm and these signals were risen as Increasing lipid contents of Alaska pollack surimi as samely protein. SEE and SEP were 0.319, 0,353, respectively. In starch analysis using NIR the signals of starch distinctly changed at wavelength of 1,450 nm and 1,950 nm. Collected values of SEE and SEP were 0.304 and 0.318, respectively and the range of errors was $0.0186\~0.6470$ in starch contents.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.3
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• pp.301-307
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• 2013

This study was evaluated high end research grade Near Infrared Reflectance Spectrophotometer (NIRS) to field grade multiple Near Infrared Reflectance Spectrophotometer (NIRS) for rapid analysis at fresh rice leaf at sight with 238 samples of fresh rice leaf during year 2012, collected Jeollabuk-do for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with 400 nm ~ 2500 nm during from year 2003 to year 2009, seven years collected fresh rice leaf database then trim and fit to field grade NIRS with 1200 nm ~ 2400 nm then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.005% differences, rapidly analysis for chemical constituents, Total nitrogen in fresh rice leaf within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless last during more than 8 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of fresh rice leaf analysis with NIRS at sight. Especially the agriculture products such as rice will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods global distance (GD) and neighbour distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.