• KOREAN JOURNAL OF CROP SCIENCE
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• v.41 no.3
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• pp.354-361
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• 1996

Near Infrared Reflectance Spectroscopy(NIRS) is accepted as today's most versatile method for rapid chemical analysis. The technique offers rapid multicomponent analysis. This study was conducted to improve the efficiency of quality analysis in covered barley grain, and to search for the effects of chemical components variation in covered barley grain on NIRS. Among the three groups with different range in the contents, each equation for starch contents increased standard error of prediction(SEP) and increased correlation coefficient from 0.872 to 0.883. According as, $\beta$-glucan and protein contents decreased SEP and increased correlation coefficient by expanded chemical components variation. Effective equation for ash contents analysis was obtained from group 3. Among the covered barley chemical components, starch and ash contents were required to conduct futher studies in term of accuracy and variation of contents. It was concluded that NIRS method would be applicable for the rapid determination of $\beta$-glucan and protein contents in covered barley grains.

• Journal of The Korean Society of Grassland and Forage Science
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• v.33 no.3
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• pp.177-184
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• 2013

This work was conducted to assess the use of Near-infrared reflectance spectroscopy (NIRS) as a technique to analyze nutritional constituents of Distillers dried grain with solubles (DDGS) and corn quickly and accurately, and to apply an NIRS-based indium gallium arsenide array detector, rather than a NIRS-based scanning system, to collect spectra and induce and analyze calibration equations using equipment which is better suited to field application. As a technique to induce calibration equations, Partial Least Squares (PLS) was used, and for better accuracy, various mathematical transformations were applied. A multivariate outlier detection method was applied to induce calibration equations, and, as a result, the way of structuring a calibration set significantly affected prediction accuracy. The prediction of nutritional constituents of distillers dried grains with solubles resulted in the following: moisture ($R^2$=0.80), crude protein ($R^2$=0.71), crude fat ($R^2$=0.80), crude fiber ($R^2$=0.32), and crude ash ($R^2$=0.72). All constituents except crude fiber showed good results. The prediction of nutritional constituents of corn resulted in the following: moisture ($R^2$=0.79), crude protein ($R^2$=0.61), crude fat ($R^2$=0.79), crude fiber ($R^2$=0.63), and crude ash ($R^2$=0.75). Therefore, all constituents except for crude fat and crude fiber were predicted for their chemical composition of DDGS and corn through Near-infrared reflectance spectroscopy.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.1
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• pp.29-34
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• 2012

The objective of this study was to rapidly evaluate fatty acids in a collection of millet (Panicum miliaceum subsp. miliaceum) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour ($n$=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.89, 0.89, 0.89, and 0.92 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2$=0.64, 0.90, 0.79, and 0.89 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). Standard deviation/standard errors of cross-validation (SD/SECV) values were close to 3 (2.62, 2.40, 1.85, and 2.23 for palmitic acid, oleic acid, linoleic acid, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic and total fatty acids characterizing millet germplasm. Among the samples, IT153514 showed an especially high content of fatty acids ($48.14mg\;g^{-1}$), whereas IT123909 had a very low content ($34.44mg\;g^{-1}$).

• Korean Journal of Breeding Science
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• v.42 no.5
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• pp.448-454
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• 2010

The objective of this study was to rapidly evaluate fatty acids in a collection of foxtail millet (Setaria italica (L.) P. Beauv) of different origins so that this information could be disseminated to breeders to advance germplasm use and breeding. To develop the calibration equations for rapid and nondestructive evaluation of fatty acid content, near-infrared reflectance spectroscopy (NIRs) spectra (1104-2494 nm) of samples ground into flour (n=100) were obtained using a dispersive spectrometer. A modified partial least-squares model was developed to predict each component. For foxtail millet germplasm, our models returned coefficients of determination ($R^2$) of 0.91, 0.89, 0.98 and 0.98 for strearic acid, oleic acid, linoleic acid, and total fatty acids, respectively. The prediction of the external validation set (n=10) showed significant correlation between references values and NIRs values ($r^2=0.97$, 0.91, 0.99 for oleic, linoleic, and total fatty acids, respectively). Standard deviation/standard error of cross-validation (SD/SECV) values were greater than 3 (3.11, 5.45, and 7.50 for oleic, linoleic, and total fatty acids, respectively). These results indicate that these NIRs equations are functional for the mass screening and rapid quantification of the oleic, linolenic, and total fatty acids characterizing foxtail millet germplasm. Among the samples, IT153491 showed an especially high content of fatty acids ($84.06mg\;g^{-1}$), whereas IT188096 had a very low content ($29.92mg\;g^{-1}$).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2122-2122
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• 2001

The ultra-high pressure technology fur the preservation of foods is under intense research to evaluate its potential as an alternative or complementary process to traditional methods of food preservation. Traditional processing methods usually need a large amount of energy, may cause unwanted reactions in the food, leading to cooked flavor and loss of vitamins, etc. The application of ultra-high hydrostatic pressure for food processing consists of subjecting the food to pressures in the range of 100-1000 ㎫. The ultra-high pressure inactivates the microorganisms and some enzymes, promotes the germination of spores and extends the shelf-life of the foods. This new technology follows the “minimal processing” concept minimizing the quality degradation, saving the vitamins, essential nutrients and flavors as well as utilizing less energy. We joined the research team at our University involved in the mentioned technology using an ultra-high pressure equipment, recording of the near infrared spectra and signal response of a chemosensor array (electronic nose) of their meat (beef and pork), vegetable and fruit samples exposed to different pressure. The results of our investigations achieved by evaluating the measured data using PCA and PQS methods will be presented.

• Journal of the Korean Applied Science and Technology
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• v.16 no.2
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• pp.155-161
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• 1999

Red pepper powder (Capsicum annum L.) is an important seasoning as a kimchi ingredient in korea and most korean consumer tend to eat the korean red pepper powder as the better than other oriental country such as China. Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of red pepper powder. The objective of this study is to determine if NIR technique could be used to discriminate between the korean red pepper powder and non-korean red pepper powder according to seed content and maxing ratio in red pepper powder by using the new method. Rapid, precise and nondestructive analysis method for determination of the geographical origin of red pepper powder by near infrared spectroscopy and chemometrics were performed. It has been observed discriminant analysis with PLS is adequate to determinate the geographical origin of red pepper powder. It tend to difficult the discrimination of geographical origin according to increase the seed content of red pepper powder. The accuracy of discrimination in mixed red pepper powder was range from 95.2% to 100%.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.7
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• pp.1036-1040
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• 2005

Near-infrared reflectance spectroscopic (NIRS) calibrations were developed for accurate and fast prediction of whole broiler chicken carcass composition. The Feed and Forage Foss systems Model 5000 Reflectance Transport Model 5000 with near-infrared reflectance spectroscopy (NIRS)-WinISI II windows software was used for this purpose. One equation was developed for the prediction of each carcass component. One hundred and fifty freeze dried broiler whole carcass samples were ground in a Cyclotech 1,093 sample mill and analyzed for dry matter, protein, fat, calcium and phosphate. Samples were divided into two sets: a calibration set from which equations were derived and a prediction set used to validate these equations. The chemical analysis values (mean${\pm}$SD) were calculated based on dry matter basis as follows: dry matter: 33.41${\pm}$2.78 (range: 26.41-43.47), protein: 54.04${\pm}$6.63 (range: 36.20-76.09), fat 35.44${\pm}$8.34 (range: 7.50-55.03), calcium 2.55${\pm}$0.65 (range: 0.99-4.41), phosphorus 1.38${\pm}$0.26 (range: 0.60-2.28). One hundred and three samples were used to calibrate the equations and prediction values. The software used was modified to obtain partial least square regression statistics, as it is the most suitable for natural products analysis. The coefficients of determination ($R^2$) and the standard errors of prediction were 0.82 and 1.83 for the dry matter, 0.96 and 1.98 for protein, 0.99 and 1.07 for fat, 0.90 and 0.30 for calcium and 0.91 and 0.11 for phosphorus, respectively. The present study indicated that NIRS can be calibrated to predict the whole broiler carcass chemical composition, including minerals in a rapid, accurate, and cost effective manner. It neither requires skilled operators nor generates hazardous waste. These findings may have practical importance to improve instrumental procedures for quick evaluation of broiler carcass composition.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.1-6
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• 2006

The purpose of this study is to develop to portable near infrared analyzer measuring the sugar content of the fruits on a tree before harvesting ones. The portable near infrared system consists of a tungsten lamp, a coaxial optical fiber bundle and a multi-channel detector, which has 256 pixels and a concave transmission grating. Reflectance NIR spectra of orange were recorded by using a coaxial optical fiber bundle. The spectra were collected over the spectral range $400{\sim}1100nm$. Partial least squares regression(PLSR) was applied for a calibration and validation for determination of sugar contents. The multiple correlation coefficient was 0.99 and standard errors of calibration(SEC) was 0.069 brix. The calibration model predicted the sugar content for validation set with standard errors of prediction(SEP) of 0.092 brix. The sugar content in fruits was successfully quantified using the portable near infrared analyzer.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.304-309
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• 2006

Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1132-1132
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• 2001

This work is a further development of the method created by G. Krivoshiev in 1996 for elimination of peel interference and prediction of fruit flesh optical density. In this investigation, as it was earlier, the objects are observed as being structured by three successive layer “AlongrightarrowOlongrightarrowB” denoting “peel-flesh-peel”. In the first version of the method the transmittances of the surface layers A and B were measured according to Kubelka-Munk theory by means of their diffuse reflectance. At that the overall transmittance T was approximated in the form of a multiplication approximation being valid for plane-parallel layers of a non-scattering material. In this work this approximation was done away with applying the theory of discontinuum, respectively Benfor's equations. As a result two mathematical models were created for non-destructive prediction of fruit flesh optical density. These models are different from the ones based solely on Kubelka-Munk theory, the destruction being marked by the terms 1n (1 - $R_{A}R_{0}$) and 1n (1 - $R_{A}R_{B}$), where: $R_{A}$ and $R_{B}$ are reflectance values for the surface layers A and B; $R_{0}$ is the average reflectance of the internal layer that could be obtained empirically by means of a preliminary measurement of sufficiently large number of physically peeled fruits of a given species and variety.