• Applied Chemistry for Engineering
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• v.31 no.1
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• pp.43-48
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• 2020

Fe₂O₃ nanoparticles with the mixed structure of cubic and nanorod were synthesized by precipitation, hydrothermal, sol-gel method, etching process and heat treatment. Fe₂O₃/TiO₂ core-shell (CS) of type Fe₂O₃@TiO₂ composite was fabricated on a 20 nm nanolayer of TiO₂ coated on the surface of Fe₂O₃ nanoparticles. Fe₂O₃/TiO₂ yolk-shell (YS) composite was prepared by chemical etching and heat treatment of Fe₂O₃/TiO₂ CS nanoparticles. Physical properties of Fe₂O₃, Fe₂O₃@TiO₂ CS and Fe₂O₃@TiO₂ YS nanoparticles were characterized by FE-SEM, HR-TEM and X-ray diffraction. The solar reflectance, commission internationale de l'Elcairage (CIE) color coordinate and heat shield temperatures of Fe₂O₃, CS and YS type Fe₂O₃@TiO₂ pigments filled with poly acrylate (PA) paints were investigated by UV-Vis-NIR spectrometer and homemade heat shield temperature measuring device. The Fe₂O₃@TiO₂ YS red pigment filled PA composite exhibited excellent near infrared light reflecting performance and also reduced the heat shield temperature of 13 ℃ than that of Fe₂O₃ filled counterparts.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Korean Journal of Plant Resources
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• v.23 no.4
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• pp.386-392
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• 2010

This study was done to measure the color and catechins contents in processed teas using the whole bands (400~2500 nm) with near-infrared spectroscopy(NIRS). The powder colors of 109 processed teas were measured with a colorimeter. The a/b ratios in Hunter color scale in processed teas accounted for about 98.9% of the variation in the fermentation degree(FD), indicating that the a/b ratio was a very useful trait for assessing fermentation degree. Also tea powders were scanned in the visible bands used with NIRSystem. The calibration equations for powder colors were developed using the regression method of modified partial least squares(MPLS) with the internal cross validation. The equations had low SECV (standard errors of cross-validation), and high $R^2$ (coefficient of determination in calibration) values with 0.996~1.00, indicating that the visible bands(400~700 nm) with NIRS could be used to rapidly measure the variables related to powder color and fermentation degree. Also another powders of 137 processed teas were scanned at 780~2500 nm bands in the reflectance mode. The calibration equations were developed using the regression method of MPLS with the internal cross validation. The equations had low SECV, and high $R^2$ (0.896~0.983) values, showing that NIRS could be used to rapidly discriminate the contents of EGC($R^2$=0.919), EC(0.896), EGCg(0.978), ECg(0.905) and total catechins(0.983) in processed teas with high precision and ease.