• Korean Journal of Environmental Agriculture
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• v.17 no.1
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• pp.54-58
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• 1998

This experiment was conducted to find out the effects of fermented compost using cattle manure and Autoclaved Lightweight Concrete(ALC) waste and duck raising in rice growing paddy fields on growth and quality of rice. By application of fermented compost of cattle manure incoporated ALC waste with amount of 2,000kg/10a, rice yield was reduced 2.9%, and 4.1% in 1,000kg/10a of compost with raising ducks plots as compared with application of standard level of chemical fertilizer. The ratio of head rice was slightly high in plots of compost application and white-belly kemeled rice was reduced by application of $1,500{\sim}2000kg/10a$ compost. The ratio of Mg/K was the highest in application of 1,000kg compost with raising duck. Efficiency of weed control by raising duck with free hexbiades was sufficient and their effects showed no difference between raising duck plots and herbidde plot.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.271-278
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• 2021

Azolla is a genus of small aquatic ferns native to Asia, Africa, and America. Azolla is potentially significant as a nitrogen source in agriculture, particularly in conjunction with rice (Oryza sativa L.) cultivation. In addition, Azolla may either control weeds or act as a weed depending on management; therefore, we aimed to determine the effect of Azolla incorporation on weed (e.g., Monochoria vaginalis, Rotala indica, Aeschynomene indica, and Cyperus amuricus) control and its other benefits during rice cultivation. The effects of Azolla on weed emergence were evaluated based on plot area coverage by the Azolla mat, which appears as a green sheet over water, and the rate of weed emergence in paddy field. Weed occurrence was investigated 40 days after Azolla inoculation. Soil samples from the experimental plots were collected following harvest in 2014-2015, and analyzed. Moreover, rice growth, yield, and grain quality were measured. Azolla suppressed weed growth by 72%. Azolla mat incorporation in rice fields suppressed weed growth by over 60%. In addition, Azolla promoted nitrogen fixation. Compared with nitrogen management using chemical fertilizers, Azolla incorporation showed the potential for various positive effects, including the improvement of soil fertility by increasing total nitrogen, and organic matter content. Rice grown with Azolla maintained its yield without additional herbicide treatment. Moreover, the palatability of cooked rice was better when grown with Azolla.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.1-8
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• 2019

Pintail (Anas acuta) is the major wintering bird in South Korea and known as a major mediator of the highly pathogenic avian influenza (HPAI). Pintail migrates long distances between Russian Siberia and Korea. This species prefers a rice paddy area as their winter habitat. The purpose of this study is to provide the data necessary for the conservation and management of bird habitats in Korea by understanding the wintering home-range and habitat of pintail in Korea. We captured six pintails using a cannon-net in the winter of 2015 and attached the GPS-mobile phone based telemetry (WT-300) on them to study the wintering home-range and wintering habitat. We analyzed the tracking location data using ArcGIS 9.0 Animal Movement Extension and calculated Kernel Density Estimation (KDE) and Minimum Convex Polygon (MCP). The average home-range in the wintering ground analyzed by MCP was $677.3km^2$ (SD=130.2, n=6) while the maximum and minimum were $847.7km^2$ and $467.5km^2$, respectively. Extents of home-range analyzed by KDE were $194.7km^2$ (KDE 90%), $77.4km^2$ (KDE 70%), and $35.3km^2$ (KDE 50%). The pintails mostly used both sea and paddy field as habitat in the winter season and utilized paddy fields more during the nighttime and than the daytime. We concluded that the home-range and habitat of pintails in the winter could be used as the reference data for the preservation of species, management of habitats, and coping with a breakout of HPAI.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.73-83
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• 2007

Network modeling of irrigation system that links irrigation facilities with stream is necessary to establish complicated rural water management system and to manage agricultural water effectively. This study attempted a network modeling for an agricultural water district called "ANGO" located in Anseongcheon watershed by connecting ArcHydro Model developed to control geographical information data in the field of water resources and AWDS(Agricultural Water Demand & Supply Estimation System) developed by KRC (Korea Rural Community & Agriculture Corporation). Network modeling was embodied by build topology between spatial objects of total 70 agricultural irrigation facilities (24 reservoirs, 18 pumping stations, 28 weirs) and stream network using ArcHydro Model. In addition, new menus were added in ArcGIS system for query and visualization of text-based AWDS outputs such as irrigation facilities information, water demand and supply analysis.

• KSBB Journal
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• v.31 no.3
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• pp.158-164
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• 2016

Plant growth promoting (PGP) hormones, which are produced in a small quantity by bacteria, affect in plant growth and development. PGPs play an important role on the crop productivity in agricultural field. In this study, a photosynthetic bacterial strain producing the PGP was isolated from paddy soil. Bacterial isolate was gram negative, rod-shaped and motility positive. From the 16s rRNA gene sequence analysis, the isolate was identified as Rhodobacter capsulatus PS-2. The mass cultivation of R. capsulatus PS-2 was optimized by considering of the carbon, nitrogen and inorganic salt sources. Optimal medium composition was determined as Na-succinate 4.5 g, yeast extract 5 g, $K_2HPO_4$ 1 g, $MgSO_4$ 5 g, per liter. From the result of 500 L fermentation for 2 days using the optimal medium, the viable cells were $8.7{\times}10^9cfu/mL$. R. capsulatus PS-2 strain produced the carotenoid and indole-3-acetic acid (IAA). The carotenoid extraction and quantitative analysis were performed by HCl-assisting method. Total carotenoid contents from R. capsulatus PS-2 culture broth were measured as $7.02{\pm}0.04$ and $6.93{\pm}0.05mg/L$ under photoheterotrophic and chemoheterotrophic conditions, respectively. To measure the productivity of IAA, colorimetric method was employed using Salkowski reagent at optical density 535 nm. The results showed that the highest content of IAA was $197.44{\pm}5.92mg/L$ in the optimal medium supplemented with 0.3% tryptophan.

• Korean Journal of Microbiology
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• v.38 no.1
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• pp.1-6
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• 2002

$\alpha$-Amylase producing bacteria were isolated from activated sludge of corn processing wastewater plant and paddy field soil samples and selected by the direct iodine reaction. The isolate was identified as Bacillus sp. after morphology, API system and fatty acid analyses. To enchance $\alpha$-amylase productivity, a successive mutation of Bacillus sp. AIV 19 was performed using the treatment of nitrosoguanidine(NTG).The mutant, Bacillus sp. AIV 1940, showed about 1.8-fold level of amylase activity compared with parental strain. The isolate was Gram-positive and rod (2.8-3.0 $\mu$m long, 0.5-0.6 $\mu$m wide) type. The strain increased the bacterial mass at 3000 mg/l starch concentration. Organic substance removal rate was 40.2, 72.3% respectively after 1 and 3 day reaction using starch synthetic wastewater (intial CODcr was 4,455 mg/l).

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.320-326
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• 2016

From the perspective of climate-smart agriculture, it is becoming more critical to accurately estimate the amount of greenhouse gas emissions in the agricultural sector. In order to accurately ascertain the methane emissions from rice paddies, which account for a significant portion of the emission from the agricultural sector, we used the data from the 2010 Agriculture, Forestry and Fisheries Census, the revised water management scaling factors and their calculation program. In order to facilitate the analyses and understanding, the results were mapped using the ArcGIS software. The fact that the validation of the mapped values against the actual field measurements at one site showed little difference encourages the necessity to further this study. The administrative districts-based map of methane emission can help clearly identify the regional differences. Furthermore, the analysis of their major controlling factors will provide important scientific basis for the practical policy makings for methane mitigation.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.73-83
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• 2020

Agricultural drought is a natural phenomenon that is difficult to observe and quantitatively express, and agricultural water use is high and usage patterns are diverse, so even if there is a lack of rainfall. The frequency and severity of agricultural drought are increased during the irrigation period where the demand for agricultural water is generated, and reasonable and efficient management of agricultural water for stable water supply is required. As one method to solve the water shortage of agricultural water in an unstructured method, it is necessary to analyze the appropriate supply amount and supply method through simulation from the intake works to the canals organization and paddy field. In this study, irrigation efficiency was analyzed for irrigation systems from April to September over the past three years from the Musu Reservoir located in Jincheon-gun, Chungcheongbuk-do and Pungjeon Reservoir located in Seosan-si, Chungcheongnam-do. SWMM (Storm Water Management Model) was used to collect agricultural water, and irrigation efficiency analysis was conducted using adequacy indicators, and water supply vulnerability. The results of the agricultural water distribution simulation, irrigation efficiency and water supply vulnerability assessment are thought to help the overall understanding of the agricultural water supply and the efficient water management through preliminary analysis of the methods of agricultural water supply in case of drought events.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.569-579
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• 2013

In this study, land-cover classification was implemented using features extracted from multi-temporal SAR data through 3D wavelet transform and the applicability of the 3D wavelet transform as a feature extraction approach was evaluated. The feature extraction stage based on 3D wavelet transform was first carried out before the classification and the extracted features were used as input for land-cover classification. For a comparison purpose, original image data without the feature extraction stage and Principal Component Analysis (PCA) based features were also classified. Multi-temporal Radarsat-1 data acquired at Dangjin, Korea was used for this experiment and five land-cover classes including paddy fields, dry fields, forest, water, and built up areas were considered for classification. According to the discrimination capability analysis, the characteristics of dry field and forest were similar, so it was very difficult to distinguish these two classes. When using wavelet-based features, classification accuracy was generally improved except built-up class. Especially the improvement of accuracy for dry field and forest classes was achieved. This improvement may be attributed to the wavelet transform procedure decomposing multi-temporal data not only temporally but also spatially. This experiment result shows that 3D wavelet transform would be an effective tool for feature extraction from multi-temporal data although this procedure should be tested to other sensors or other areas through extensive experiments.