• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 1997.10a
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• pp.28-28
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• 1997

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2000.11a
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• pp.124-137
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• 2000

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 1997.04a
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• pp.19-19
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• 1997

• 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.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.4
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• pp.273-277
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• 2001

Traditional methods of chemical analysis for the soil properties take time and produce harmful waste. The purpose of this research was to evaluate an NIR technique for measuring some soil properties that are rapid and accurate in soil fertility assessments. The NIR instrument (InfraAlyzer 500, Bran & Luebbe Co.) was used for obtaining spectral data from 140 finely ground soil for calibrations and validation estimating pH, CEC, extractable Ca, Mg, K, $SiO_2$, humic acid and EC. Partial least square regression analysis was used to develop a calibration of NIR spectroscopy method. The results indicated that NIR spectroscopy could be used as a routine nondestructive method quantitatively determining soil chemical properties quickly. However the NIR technique may require sample preparation to obtain even diffuse reflection spectra from the soil and data manipulations to obtain optimal predictions.

• Proceedings of the Korean Society of Tobacco Science Conference
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• 1999.10a
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• pp.15-15
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• 1999

• Korean Journal of Food Science and Technology
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• v.28 no.5
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• pp.916-921
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• 1996

This study was conducted to measure fat contents of potatochips by near infrared spectroscopy (NIRS). Both potatochip powder and potatochips were used to find correlations between the absorbance at certain wavelengths find the fat contents. Based on the correlation analysis, linear regression models predicting the fat contents were developed to predict the fat contents. Artificial neural network (ANN) models were also developed. Predicted values were compared to the measured ones. The regression and the ANN model predicting the fat contents of potatochip powder had determination coefficients of 0.93 and 0.92, and standard errors of prediction (SEP) of 1.29% and 1.17%, respectively. The correlation analysis of potatochips showed that the determination coefficients were low. Therefore, the fat contents of not potatochips but potatochip powder could be measured by NIRS.

• Food Science and Preservation
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• v.24 no.1
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• pp.145-152
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• 2017

In this study, near infrared (NIR) spectroscopy known as a non-destructive analysis technique was applied to investigate peptide cleavage and consequent release of amino acids in soybean lumps as affected by its moisture content and incubation time during fermentation at 25 for 3 weeks. The NIR spectra of the soybean lump semi-dried and soaked in saline water showed that absorption intensity around 1,400 nm originating from hydrogen bonds of water decreased and absorption band shifted to 1,430 nm as moisture content decreased during incubation at 25 for 3 weeks. In addition, absorption around 2,050 nm which was assigned to amino groups increased as incubation time increased. NIR spectra data from 1,000 to 2,250 nm showed higher accuracy in the discriminant analysis between outside and inside parts of fermented soybean lumps than visible spectra result. NIR spectroscopy for the amino acid and moisture contents in traditional fermented soybean lumps showed relatively good accuracy with the multiple correlation coefficient ($R^2$) of 0.91 and 0.81, respectively, and root mean square error of cross validation (RMSECv) of 0.23 and 0.83%, respectively, in partial least square regression (PLSR). These results indicate that NIR spectral observations could be applicable to control the fermentation process for preparation of soybean products.

• Journal of The Korean Society of Grassland and Forage Science
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• v.31 no.4
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• pp.415-422
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• 2011

This study evaluated the feasibility of using a portable near infrared reflectance spectrometer working in the 900~1,600 nm range for the measurement of quality-related parameters (moisture, pH, Acid detergent fiber (ADF), Neutral detergent fiber (NDF), Crude protein (CP), lactic acid) in intact silage. The calibration result for the Phazir (handheld, Polychromix) was compared with the result for the Spectrastar (Lab. based, Unity). A total of 67 Italian ryegrass silages were used to build calibration models using different spectral signal pre-treatments and the partial least squares regression (PLS) method. The good calibration statistics in two instruments was obtained for moisture content of Italian ryegrass silages with over $R^2$ = 0.95. The Phazir spectrometer was less accurate in measuring of ADF, NDF and CP contents. The Spectrastar instrument yielded greater precision for pH and lactic acid content; statistic values were over $R^2$ = 0.82 and the standard error of calibration (SEC) = 0.21% and 0.24%. Thus, the NIR measurement of forage quality in the field by portable NIR analyzers was shown not to be feasible, but additional investigations are required to discern the key instrumental and operational parameters that may influence the portable NIR measurement.