• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.63-73
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• 2016

How effectively a wind farm captures high market prices can greatly influence a wind farm's viability. This research identifies and creates an understanding of the effects that result in various capture prices (average revenue earned per unit of generation) that can be seen among different wind farms, in the current and future competitive SMP (System Marginal Price) market in South Korea. Through the use of a neural network to simulate changes in SMP caused by increased renewables, based on the Korea Institute of Energy Research's extensive wind resource database for South Korea, the variances in current and future capture prices are modelled and analyzed for both onshore and offshore wind power generation. Simulation results shows a spread in capture price of 5.5% for the year 2035 that depends on both a locations wind characteristics and the generations' correlation with other wind power generation. Wind characteristics include the generations' correlation with SMP price, diurnal profile shape, and capacity factor. The wind revenue cannibalization effect reduces the capture price obtained by wind power generation that is located close to a substantial amount of other wind power generation. In onshore locations wind characteristics can differ significantly/ Hence it is recommended that possible wind development sites have suitable diurnal profiles that effectively capture high SMP prices. Also, as increasing wind power capacity becomes installed in South Korea, it is recommended that wind power generation be located in regions far from the expected wind power generation 'hotspots' in the future. Hence, a suitable site along the east mountain ridges of South Korea is predicted to be extremely effective in attaining high SMP capture prices. Attention to these factors will increase the revenues obtained by wind power generation in a competitive electricity market.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.387-397
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• 2021

Most of Korea's agricultural water is supplied by reservoirs, so dependence on them is very high. Accordingly, it is important to reduce this dependence and provide a stable agricultural water supply by utilizing an applicable alternative water source. Therefore, in this work, scenarios for different land uses were constructed, and an optimal water supply plan using rainwater and reused sewage water - which are alternative water sources - was created. A study was also conducted to determine the optimal capacity of a rainwater facility. From the analysis, a stable water supply was achieved in the scenario of maximum utilization of rainwater by changing an existing paddy area to a greenhouse area, and about 0.82 ton of flow capacity was required for 1 mm of rainfall on farms utilizing rainwater. As a result of analyzing the optimal scenario to derive the ratio of the storage capacity per unit water collection area, the rainwater storage capacity determined through MODSIM and the storage capacity determined through actual monitoring showed similar results, about 31 and 32 %, respectively, and the optimal capacity of rainwater facilities was calculated to be about 5,796,000-6,182,400 ton.

• The Korean Journal of Mycology
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• v.49 no.3
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• pp.405-412
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• 2021

Wolfiporia cocos is an important medicinal fungus that has been used in regions of Northeast Asia including Korea, Japan, and China. W. cocos is classified in Korea into two types (red bokryeong and white bokryeong) based on the internal colors (yellow orange-pale pink and white) of the sclerotium. Generally, the W. cocos type cultivated on farms produces white sclerotium. In this study, we endeavored to select strains that form sclerotium in sawdust medium using 2-way cross-breeding among two cultivated strains and three wild strains. Monospores were isolated from the fruiting bodies of cultivated and wild strains on potato dextrose agar. Thirty-nine strains of 338 hybrid strains isolated formed sclerotia with white or yellow colors upon culture for 3 months in Pinus densiflora sawdust medium. Selection for sclerotium forming strains using sawdust culture follows a very simple and easy procedure that is presented for the first time in this paper. We plan to test selected strains in the field to aid in developing new varieties for the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.107-119
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• 2019

As the development of ICT and integration technology, many changes and innovations in agriculture field are implemented. The agricultural sector has shifted from a traditional industry to a new industrial form called the 6th industry combined with various advanced technologies such as ICT and IT. Various approaches have been attempted to analyze and predict crops based on spatial information. In particular, a variety of research has been carried out recently for crop cultivation and smart farms using drones. The goal of this study was to establish an agricultural drought monitoring system using drones to produce scientific and objective indicators of drought. A soil moisture sensor was installed in the drought area and checked the actual soil moisture. The soil moisture data was used by the reference value to compare and analyze the temperature and NDVI established by drones. The soil temperature by the drone thermal image sensor and the NDVI by the drone hyperspectral was analyzed the correlation between crop condition and soil moisture in study area. To verify this, the actual soil moisture was calculated using the soil moisture measurement sensor installed in the target area and compared with the drone performance. This study using drone drought monitoring system may enhance to promote the crop data and to save time and economy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.184-192
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• 2021

Domestic agriculture is facing real problems, such as a decrease in the population in rural areas, a shortage of labor due to an aging population, and increased risks due to the deepening of climate change. Smart farming technology is being developed to solve these problems. In the development of smart agricultural technology, irrigation control plays an important role in creating an optimal growth environment and is an important issue in terms of environmental protection. This paper is about the study of collecting and analyzing the rhizosphere environmental data of domestic paprika farms for the purpose of improving the quality of crops, reducing production costs, and increasing production. Irrigation control modeling presented in this paper Control modeling is to graphically present changes in a medium weight, feed, and drainage due to regional climatic features. To derive the graph, the parameters were determined through data collection and analysis, and the suggested irrigation control modeling method was applied to the collected rhizosphere environmental data to control irrigation in 6 regions (Gangwon-do, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, and Gyeongnam). The parameters were obtained and graphs were derived from them. After that, a study was conducted to analyze the derived parameters to verify the validity of the irrigation control modeling method and to correlate them with climatic features (average temperature and precipitation).

• Journal of agriculture & life science
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• v.51 no.4
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• pp.139-147
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• 2017

This study was carried out in order to reduce the amount of sawdust for recycling the generated manure from livestock farms, and to investigate the effects on the reducing usage of sawdust and quality of produced compost. To do this, a cylindrical horizontal composting device were used in the experiments and compost was analyzed for judging produce compost quality. The experiment was carried out separately under different cases of operational control conditions. The first case was produced by using sawdust and pig manure mixture(Test-1); the second case was produced by using sawdust, pig manure and the previously produced compost(Test-2). In the second case, Except for some heavy metal content, The water content and C/N ratio were found to be suitable for fertilizer process specification of the RDA(Rural Development Administration) and it was found to reduce the sawdust 1.25tons usage.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.35-43
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• 2021

Citrus quality is generally determined by its sugar content and acidity. In particular, sugar content is a very important factor because it determines the taste of citrus. Currently, the most commonly used method of measuring citrus sugar content in farms is a portable juiced sugar meter and a non-destructive sugar meter. This method can be easily measured by individuals, but the accuracy of the sugar content is inferior to that of the citrus NongHyup official machine. In particular, there is an error difference of 0.5 Brix or more, which is still insufficient for use in the field. Therefore, in this paper, we propose an AI model that predicts the citrus sugar content of unmeasured days within the error range of 0.5 Brix or less based on the previously collected citrus sugar content and meteorological data (average temperature, humidity, rainfall, solar radiation, and average wind speed). In addition, it was confirmed that the prediction model proposed through performance evaluation had an mean absolute error of 0.1154 for Seongsan area and 0.1983 for the Hawon area in Jeju Island. Lastly, the proposed model supports an error difference of less than 0.5 Brix and is a technology that supports predictive measurement, so it is expected that its usability will be highly progressive.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.378-385
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• 2021

The production of plum jangachi requires the cleaning of plums, immersion in saltwater, separation of seed and pulp, removal of impurities, and addition of sugar. In most farms, the separation of plum seed and pulp is carried out manually, requiring considerable labor, which is why plum jangachi is expensive. To solve this problem, this study designed and manufactured automatic, semi-automatic plum seed and pulp separators. During the design process, the characteristics were compared, and the machine power was determined through on-site test after manufacture. As a result, automatic machines used plums 180° arrayed and six reverse-edged blades, semi-automated plums 180° arrayed, and six blades, each with a 68% and 57% pulp recovery rate and a machine power of 80 kg/h and 62 kg/h respectively. Overall, the mechanization of plum processed food will reduce labor and increase the market value of plums compared to the previous method.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.87-97
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• 2021

To investigate the current pest management status in Korea, a survey was conducted from 151 students and graduates in the Korea National College of Agriculture and Fisheries (KNCAF) by on-line. The questionnaire consists of two divisions, basic questions and pest control questions. The basic questions were including the respondent's age, academic status, cultivating crops and cultivating area. The pest control questions were including pest control methods, pesticide selection rationale, and pest forecasting methods. As a summary of basic questions, the respondents in their 20s accounted for 91.2%. Moreover, 34.5% of the respondents had over 3 hectares of cultivating area. The cultivating methods were differed by cultivating crops. As a summary of pest control questions, major control methods were using the conventional chemicals (>66%). To understand the pesticide selection rationale, farmers/respondents made their own decisions based on existing control techniques (30%) or depended on the decisions of pesticide vendors (29%). As for the pest forecasting method, it was mainly conducted by the Rural Development Administration affiliated organization (29%) and the National Crop Pest Management System (27%). Regarding the reliability of the pest diagnosis and pesticide prescription of pesticide vendors, 97% of the respondents marked above average. However, there was no choice on strong reliability. Interestingly, 79% of the respondents agreed to train experts for pest diagnosis and pesticide prescription with high necessity and, in particular, 47% of respondents were very strongly supported. These results suggest that the farmers might be need more qualified experts in pest diagnosis and pesticide prescriptions. Taken together, these survey results would provide important information to understand the current status of pest management by farmers' point of view and useful to set the direction of pest control.