• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.3
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• pp.244-250
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• 2008

The purpose of this study was to measure fundamental data required for the prediction of milling ratios, and to develop regression models to predict the head rice ratio of milled rice using NIR spectra of hulled rice. A total of 81 rice samples used in this study were collected from Jeongeup, Jeonbuk province in 2006. NIR spectra were measured using one mode of measurement, reflection. The reflectance spectra were measured in the wavelength region of 400-2500 nm with an NIR spectrophotometer "NIRSystems 6500" (Foss, Silverspring, USA). Calibration equations were developed by the modified partial least squares (MPLS), partial least squares (PLS), and principal components regression (PCR). Math treatments were 1-4-4-1, 1-10-10-1, 2-4-4-1, and 2-10-10-1. The software used was WinISI (Infrasoft International, State College, USA). Automatic head rice production and quality checking system used was "SY2000-AHRPQCS" (Ssangyong, Korea). The calibration was made with the first derivative and the spectrum designated was in 8 nm interval. The determination coefficients of head rice ratios were 0.8353, 0.8416 and 0.5277 for the MPLS, PLS and PCR, respectively. Those obtained with 20 nm interval were 0.8144, 0.8354 and 0.6908 for the MPLS, PLS and PCR, respectively. The calibration was made with second derivative that spectrum designated was 8 nm in interval. The determination coefficients of head rice ratios were 0.7994, 0.8017 and 0.4473 for the MPLS, PLS and PCR, respectively. Those with 20 nm interval were 0.8004, 0.8493 and 0.6609 for the MPLS, PLS and PCR, respectively. These results indicate that the accuracy of determination coefficient for MPLS and PLS is higher than that of PCR.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.3
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• pp.296-300
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• 2012

Discrimination of geographic origin of agricultural products is a important issue in Korea because the price difference between Korean domestic and imported cereals is a key among some reasons. NIRS (Near Infrared Reflectance Spectroscopy) has been applied to classify the geographical origin of soybeans. Total 135 samples (Korean domestic 92 and foreign 43) were used to obtain calibration equation through 400~2,500 nm wavelength. The math treatment with 1st derivative and 4 nm gap and the modified partial least squares(MPLS)regression was outstanding for calibration equation. The standard error of calibration and determination coefficient in calibration set(n=115) was 6.65 and 0.98, respectively. And it showed that the extra 20 samples for validation equation were identified their authentication correctly. This study describes that the application of NIRS would be possible for discrimination of geographical origin between Korean domestic and imported soybeans.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.3
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• pp.211-215
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• 2004

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to determine tocopherol and tocotrienol contents in rice bran by using NIRS system. Total 80 rice bran samples previously analyzed by HPLC were scanned by NIRS and over 60 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and coefficient of determination for tocopheyol and tocotyienol content were 0.975 and 0.984, respectively, in calibration sets. Each calibration equation was fitted to validation set that was performed with the remaining samples not included is the calibration set, which showed high positive correlation both in tocopherol and tocotrienol content file. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of tocopherol and tocotrienol contents in rice bran.

• Korean Journal of Medicinal Crop Science
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• v.10 no.5
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• pp.340-343
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• 2002

Near infrared reflectance spectroscopy (NIRS) has become widely accepted for rapid quantitative analysis of components in some crops. Our object was to determine icariin contents in whole plant of Epimedium koreanum by using an NIRS system. Total 150 plant samples previously analyzed by HPLC were scanned by NIRS and 68 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and a coefficient of determination in calibration and validation sets were 0.95 and 0.82, respectively. A comparison between NIRS estimation and HPLC value was performed with the remaining samples not included in the calibration and validation sets. Most of samples also showed a positive correlation like a validation set. Our results demonstrate that this developed NIRS equation can be practically used as a mass screening method for rapid quantification of icarin contents in Epimedium koreanum N.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.2
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• pp.106-111
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• 2001

The applicability of near infrared reflectance spectroscopy(NIRS) was tested to determine the protein and oil contents in ground soybean [Glycine max (L.) Merr.] seeds. A total of 189 soybean calibration samples and 103 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing and 1 point second smoothing) math treatment condition with SNV-D (Standard Normal Variate and Detrend) scatter correction method and entire spectrum by using MPLS (Modified Partial Least Squares) regression. In the case of oil, the best equation was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared (1100-2500nm) region by using MPLS regression. Validation of these NIRS equations showed very low bias (protein:-0.016%, oil : -0.011 %) and standard error of prediction (SEP, protein: 0.437%, oil: 0.377%) and very high coefficient of determination ($R^2$, protein: 0.985, oil : 0.965). Therefore, these NIRS equation seems reliable for determining the protein and oil content, and NIRS method could be used as a mass screening method of soybean seed.

• Korean Journal of Plant Resources
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• v.27 no.4
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• pp.286-292
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• 2014

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure baicalin, baicalein, and wogonin contents in Scutellaria baicalensis by using NIRS system. Total 63 samples previously were analyzed by HPLC, which showed baicalin, baicalein, and wogonin contents ranging 4.56 to 13.59%, 0.28 to 5.54%, and 0.50 to 1.63% with an average of 9.66%, 2.09% and 0.52%, respectively. Each sample was scanned by NIRS and calculated for calibration and validation equation. A calibration equation calculated by modified partial least squares(MPLS) regression technique was developed in which the coefficient of determination for baicalin, baicalein, and wogonin content was 0.958, 0.944, and 0.709, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in baicalin and baicalein content file. In case of wogonin, the prediction model was needed more accuracy because of low $R^2$ value in validation set. These results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of baicalin and baicalein contents in Scutellaria baicalensis.

• Journal of the Korean Society of Tobacco Science
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• v.17 no.2
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• pp.177-183
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• 1995

This study was conducted to develop the most precise NIR(near infrared spectrometric) calibration for rapid determination of chemical composition in ground samples of toasted burley tobacco using stepwise, stepup, principal component regression(PCR), partial least square(PLS) and modified partial least square(MPLS) calibration method. The number of wavelength(W) selected by stepup multiple linear regression using: second derivative spectra was as follows: total sugar(TS)-4 W, nicotine-9 W, total nitrogen(TN)-2 W, ash-8 W, total volatile base(TVB)-5 W, chlorine4 W, L of color-6 W, a of color-6 W and b of color-7 W. Comparing the calibration equations followed by each chemical components, the most precise calibration equation was MPLS for 75, a and b of color, PLS for nicotine, ash, TVB, chlorine and L of color and stepup for TN. The standard error of calibration(SEC) and standard error of performance(SEP) between result of near infrared analysis and standard laboratory analysis were 0.18, 0.40% for 75, 0.06, 0.08% for nicotine, 0.18, 0.16% for TN, 0.33, 0.46% for ash, 0.04, 0.03% for TVB, 0.08, 0.06% for chlorine, 0.54, 0.58 for L of color, 0.22, 0.22 for a of color and 0.27, 0.27 for b of color, respectively. The SEC and SEP of ash and TVB were within allowable error of standard laboratory analysis, nicotine, TN and chlorine were 1.2-2.0 times and 75 were 2.1-4.0 times larger than allowable error of standard laboratory analysis. The ratio of SEC and SEP to mean were 1.5, 1.6% for L of color, 3.7, 3.8% for a of color and 1.8, 1.8% for b of color, respectively. Key words : burley tobacco chemistry, near infrared spectroscopy.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.15-20
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• 2008

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure anthocyanin contents in black colored soybean by using NIRS system. Total 300 seed coat of black colored soybean samples previously analyzed by HPLC were scanned by NIRS and over 250 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed in which the coefficient of determination for anthocyanin pigment C3G, D3G and Pt3G content was 0.952, 0.936, and 0.833, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in C3G and D3G content file. In case Pt3G, the prediction model was needed more accuracy because of low $R^2$ value in validation set. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of C3G and D3G contents in black colored soybean.

• Journal of environmental and Sanitary engineering
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• v.22 no.4
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• pp.65-76
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• 2007

The possibility of rapid quantitative analysis of AV(Acid Value), IV(Iodine Value) and fatty acids in vegetable oils with NIRS(Near-infrared spectroscopy) was evaluated. A calibration equation calculated by MPLS regression technique was developed and correlation coefficient of determination for AV, IV, $C_{16:0},\;C_{18:0},\;C_{18:1},\;C_{18:2},\;C_{18:3},\;and\;C_{20:0}$ content were 0.9727, 0.997, 0.9805, 0.942, 0.9987, 0.9994, 0.9966, and 0.975 respectively. According to the data obtained from validation study, $R^2$ of contents of perilla, corn, soybean, rapaseed oils were 0.897, 0.993, 0.935, 0.707, 0.994, 0.996, 0.984, 0.798, SEP of contents of 0.185, 1.367, 0.899, 0.640, 1.498, 1.360, 0.476, 0.076 by MPLS. The results indicate that the NIRS procedure can potentially be used as a non-destructive analysis method for the rapid and simple measurement of AV, IV and fatty acids in vegetable oils.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.12
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.