• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.779-787
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• 2011

This study was conducted to evaluate the usefulness of ground-based remote sensing for the estimation of rice yield and application rate of N-fertilizer during growing season. Dongjin-1, Korean cultivar of rice was planted on May 30, 2006 and harvested on October 9, 2006. Chlorophyll content and LAI (leaf area index) were measured using Minolta SPAD-502 and AccuPAR model LP-80, respectively. Reflectance indices were determined with passive sensors using sunlight and four types of active sensors using modulated light, respectively. Reflectance indices and growth rate were measured three times from 29 days to 87 days after rice plating and at harvesting day. The result showed that values of growing characteristics and reflectance indices were highly correlated. Growing characteristics to show significant correlation with reflectance indices were in order of followings: fresh weight > N uptake > dry weight > height > No. of tiller > N content. Chlorophyll contents measured by chlorophyll meter (SPAD 502) showed high correlation with nitrogen concentration (r=$0.743^{**}$), although the correlation coefficients between remote sensing data and nitrogen concentration were higher. LAI was highly correlated with dry weight (r=$0.931^{**}$), but relationship between LAI and nitrogen concentration (r=$0.505^*$) was relatively low. The data of CC-passive sensor were negatively correlated with those of the near-infrared. NDVI correlation coefficients found more useful to identify the growth characteristics rather than data from single wavelength. Both passive sensor and active sensor were highly significantly correlated with growth characteristics. Consequently, quantifying the growth characteristics using reflectance indices of ground-based remote sensing could be a useful tool to determine the application rate of N fertilizer non-destructively and in real-time.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.937-943
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• 2011

In order to develop constructed wetlands for treating hydroponic wastewater in greenhouses, removal efficiencies and decomposition velocities of pollutants in constructed wetland were investigated for treating hydroponic wastewater. Removal rates of BOD, COD, SS, T-N and T-P in effluent in constructed wetlands were 88%, 79%, 92%, 64% and 92%, respectively. The decomposition velocities (K; $day^{-1}$) of pollutants in $1^{st}$ HF bed of constructed wetlands were higher in the order of SS ($0.54day^{-1}$) > BOD ($0.39day^{-1}$) > COD ($0.27day^{-1}$) > T-P ($0.26day^{-1}$) > T-N ($0.06day^{-1}$). In $1^{st}$ HF bed of constructed wetlands, the decomposition velocity of SS was rapid than that for BOD, COD, T-N and T-P in constructed wetland for treating hydroponic wastewater. The decomposition velocity (K; $day^{-1}$) of pollutants in $2^{nd}$ HF bed of constructed wetland were higher in the order of T-P ($0.52day^{-1}$) > BOD ($0.28day^{-1}$) > COD ($0.15day^{-1}$) > T-N ($0.06day^{-1}$) > SS ($0.10day^{-1}$). In $2^{nd}$ HF bed of constructed wetlands, the decomposition velocity of T-P was rapid than that for BOD, COD, SS and T-N in constructed wetland for treating hydroponic wastewater.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.328-334
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• 2021

This study was conducted to analyze the effect of fog cooling during daytime and heatpump cooling at night in greenhouses in summer. During daytime, the average temp. and RH of the control greenhouse which had shading screen were 32.1℃ and 59.4%. and the average temp. and RH of the test greenhouse which had fog cooling were 30.0℃ and 74.3%. At this time, the average outside temp. and RH were 31.4℃ and 57.7%. So, the temp. of the control was 0.7℃ higher than outside temp., but the temp. of the test was 1.4℃ lower than outside and 2.1℃ lower than control. The average RH was 74.3% in the test and 59.4% in control. The average temp. and RH of the control greenhouse which had natural ventilation at night were 25.2℃ and 85.1%, and the average temp. and RH of the test greenhouse which had heat pump cooling were 23.4℃, 82.4%. The average outside temp. and RH at night were 24.4℃ and 88.2%. The temp. of the control was 0.8℃ higher than outside temp., but the temp. of the test was 1.0℃ lower than outside and 1.8℃ lower than control. The average RH was 82.4% in test and 85.1% in control greenhouse. There was no significant difference between the plants growth eight weeks after planting. But after the cooling treatment, the values of stem diameter, plant height, chlorophyll in test were higher than control. The total yield was 81.3kg in test, 73.8kg in control, so yield of test was 10.2% higher than control. As a result of economic analysis, 142,166 won in profits occurred in control greenhouse, but 28,727 won in losses occurred in test greenhouse, indicating that cooling treatment was less economical.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.448-454
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• 2021

This study was conducted to the effect of low air temperature and light intensity conditions on yield and quality of tomato at the early stage of growth in Korea. Inplastic greenhouses, low temperature and low temperature with shade treatments were performed from 17 to 42 days after plant. Tomato growing degree days were decreased 5.5% due to cold treatment during the treatment period. Light intensity decreased 74.7% of growing degree days due to shade. After commencing treatments, the plant growth decreased by low temperature and low radiation except for height. Analysis of the yield showed that the first harvest date was the same, but the yield of the control was 3.3 times higher than low temperature with shade treatment. The cumulative yields at 87 days after transplanting were 1734, 1131, and 854 g per plant for control, low temperature, and low temperature with shade, respectively. The sugar and acidity of tomatoes did not differ between treatment and harvesting season. To investigate the photosynthetic characteristics according to the treatment, the carbon dioxide reaction curve was analyzed using the biochemical model of the photosynthetic rate. The results showed that the maximum photosynthetic rate, J (electric transportation rate), TPU (triose phosphate utilization), and R_d (dark respiration rate) did not show any difference with temperature, but were reduced by shading. Vcmax (maximum carboxylation rate) was decreased depending on the low temperature and the shade. Results indicated that low temperature and light intensity at the early growth stage can be inhibited the growth in the early stage but this phenomenon might be recovered afterward. The yield was reduced by low temperature and low intensity and there was no difference in quality.

• Journal of Mushroom
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• v.19 no.3
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• pp.166-175
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• 2021

In this study, monokaryons of "Heukari" (Pleurotus ostreatus) and "Hosan" (Pleurotus pulmonarius) were separated to remove the cell wall, and a cross-species protoplast fusion was developed through chemical treatment with polyethylene glycol. The protoplast-fused PF160306 and PF160313 strains have a culture period of 10 and 2 days shorter than that of the "Heuktari" and "Hosan" cultivars, respectively. Furthermore, the growth of the strains was faster than that of the existing cultivars. The yield was 135.9 g per bottle, which was approximately 8% higher than that of the commercially available "Hosan" cultivar; however, it was not statistically significant. A growth survey was conducted after treatment at five temperatures (15, 18, 21, 23, and 25℃). The growth of the strains accelerated with the increase in temperature. However, at 21℃, the yellow color of pileus was the brightest. Band pattern, assessed using URP Primer 7, was similar to that of the "Hosan" cultivar. The DPPH radical scavenging capacity and polyphenol content were 62.5% and 43.5 mg/mL, respectively, for "Sunjung" and 65.7% and 49.9 mg/mL, respectively, for PF160313. Furthermore, the antihypertensive activities of the "Sunjung" cultivar and PF160313 were similarly high at 74% and 75%, respectively. In conclusion, cross-species hybridization via the protoplast fusion technique can be used for obtaining primary data for mushroom breeding to develop new varieties. In addition, the protoplast fusion technique might aid in expanding the market for yellow mushrooms.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Korean Journal of Community Nutrition
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• v.26 no.5
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• pp.327-336
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• 2021

Objectives: This study was conducted to create a 3D printable snack dish model for the elderly with low food or fluid intake along with barriers towards eating. Methods: The decision was made by the hybrid-brainstorming method for creating the 3D model. Experts were assigned based on their professional areas such as clinical nutrition, food hygiene and chemical safety for the creation process. After serial feedback processes, the grape shape was suggested as the final model. After various concept sketching and making clay models, 3D-printing technology was applied to produce a prototype. Results: 3D design modeling process was conducted by SolidWorks program. After considering Dietary reference intakes for Koreans (KDRIs) and other survey data, appropriate supplementary water serving volume was decided as 285 mL which meets 30% of Adequate intake. To consider printing output conditions, this model has six grapes in one bunch with a safety lid. The FDM printer and PLA filaments were used for food hygiene and safety. To stimulate cognitive functions and interests of eating, numbers one to six was engraved on the lid of the final 3D model. Conclusions: The newly-developed 3D model was designed to increase intakes of nutrients and water in the elderly with dementia during snack time. Since dementia patients often forget to eat, engraving numbers on the grapes was conducted to stimulate cognitive function related to the swallowing and chewing process. We suggest that investigations on the types of foods or fluids are needed in the developed 3D model snack dish for future studies.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Korean Journal of Breeding Science
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• v.43 no.5
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• pp.413-421
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• 2011

The main objective of this study was to develop the multi-resistance lines to insects(brown planthopper; BPH, rice green leafhopper; GRH) and disease(blast; BL, bacterial blight; BB and rice stripe virus disease;RSV) with good grain quality and plant type by combining conventional breeding and marker assisted selection(MAS) and to eliminate the linkage drag effects between Bph1 gene and culm length, we conducted MAS of Bph1 gene in advanced backcross and double cross progenies. 'Nampyeong', 'Junam' and 'Milyang220' were used as the parent in this study. 'Milyang220' was used as the donor of brown planthopper resistance gene Bph1 with tall culm length. Two backcross progenies were developed using two recipients 'Nampyeong' carrying GRH resistance gene Grh3(t) with good grain appearance and 'Junam' harboring bacterial blight resistance gene Xa3 with short culm length. Two $BC_1$ generations were resulted from the backcrossing of the $F_1$ plants with recurrent parents 'Nampyeong' and 'Junam'. The second rounds of backcrossing($BC_2$) were derived from the cross of selected resistant $BC_1F_1$ plants based on heterozygous genotype of RM28493 linked to Bph1 gene. The double crossed population was constructed from the cross of between each heterozygous $BC_2F_1$ plants at RM28493 locus of '$Nampyeong^*3$ / Milyang220' and '$Junam^*3$ / Milyang220'., The homozygous alleles in Bph1 gene were selected using co-dominant DNA marker RM28493 in double crossed population. Eighty-five lines with multi-resistance to BL, BB, RSV, GRH and BPH were selected by bio-assay and MAS in generation of double crossing. The culm length, head rice ratio and yield of the selected multi resistance lines was ranged from 71 to 88 cm, from 51 to 93%, from 449 to 629 kg/10a. respectively. We can select a promising multi resistance line similar with 'Nampyeong' of major agronomic traits such as culm legnth, head rice ratio and yield. It was designated as Milyang265. Finally this study was developed the multi resistant varieties against to insects and diseases with the good grain quality 'Milyang265' by the advanced backcross and double cross combining MAS and it can be used as genetic resources of multi-resistance to insect and diseases in rice breeding programs.