• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.39-52
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• 2023

There is a clear need to enhance the attractiveness of rural areas by leveraging their core assets to respond to emerging mega-trends. This paper analyzes the progress of the direct payment program that has been implemented to preserve agricultural landscapes in rural areas, using spatial information data. The study identified the planting characteristics of landscape crops, spatial utilization characteristics of the system, and utilization characteristics of the system by the beneficiaries. According to the analysis, the spatial utilization characteristics of the system could be classified into eight types: tourism resources and nearby agricultural areas, designation across the entire rural area, agricultural areas around villages, large-scale agricultural areas, small-scale agricultural areas, scattered and dispersed areas, independent parcels of land, and ranches. Based on the characteristics and limitations of the landscape preservation direct payment system, this study provides directions for future rural specialized zones. The landscape preservation direct payment system focuses on income support for farmers and providing agricultural benefits in terms of public interest. Meanwhile, the landscape agricultural zone serves as a rural specialized zone, highlighting the need to explore the direction of integrated rural landscape management. It is important for farmers, as the key stakeholders, to preserve the agricultural landscape in rural areas. Forming community-level cooperatives and engaging in relevant activities are crucial for achieving this goal. In order to actively preserve the agricultural landscape, it is necessary to consider the resumption of financial support for village landscape preservation activities, along with the designation of landscape agricultural zones. There is a need to conduct a specific review and explore measures to accommodate the designated landscape complexes at the local government level. The higher the ratio of designated landscape complexes, the more agricultural landscape management based on public value has been carried out. The designation of such landscape complexes can be seen as a demand for voluntary utilization of agricultural landscapes in the region. Moreover, as the ratio of designated landscape complexes increases, it becomes evident that farmers at the village level actively participate in agricultural landscape preservation and contribute to providing public value or utilize it as a tourism resource. This highlights the need for managing agricultural landscapes at the village level within the appropriate context.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.10
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• pp.373-382
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• 2016

Under the Agricultural technology is influenced from climate that is requisite of seasonal. So this system will cover the problems and develop the agricultural industry as well. So far, the agricultural industry is developing however, it has the points of the weakness because of natural disasters such as wind risk and heavy snow. This paper designs system to change vinyl on the greenhouse. This is a preliminary study for the real-time feedback control of greenhouse. The study developed a wireless IoT sensor system based on authentic technology capacities, to integrate with the protected horticulture Management System. These system was used to evaluate the levels of the snow cover and wind through IoT devices. The existing greenhouse uses the warm water to clear snow or to change methods. This system will recover by changing the vinyl which is covered outside of the greenhouse. The points of the system is changing vinyl to spin pipe. It is contained extra vinyl. The effects of this system are minimized labor protected crops from natural disasters. For this purpose, the study first developed a wireless IoT sensor unit that integrates an MEMS device and wireless communication module. Also, the study developed an operating program that enables real-time response measurement. It will help operational and maintenance greenhouse as a result.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1467-1475
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• 2023

The public-interest direct payment program involves providing direct payments to agricultural producers and rural residents through public funds, premised on performing public functions such as environmental conservation, stable food supply, and maintaining rural communities via agricultural activities. Scientific estimation of crop cultivation areas and production levels is crucial for formulating agricultural policies linked to regulating food supply, which increasingly impacts the national economy. Conducting comprehensive on-site inspections for compliance monitoring of direct payment programs has shown very low efficiency in relation to budget and time. The expansion of areas subject to compliance monitoring and various challenges in on-site inspections necessitate streamlining current monitoring methods and devising effective strategies. As a solution, the application of Remote Sensing technology and spatial information utilization, allowing swift acquisition of necessary information for policies without overall on-site visits, is being discussed as an efficient compliance monitoring method. Therefore, this study evaluated the potential use of remote sensing for improving operational efficiency in monitoring compliance with public-interest direct payment programs. Using satellite images during farming seasons in Gimje and Hapcheon, vegetation indices and spatial variations were utilized to identify cultivated areas, presence of mixed crops, validated against on-site inspection data.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.1-14
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• 2023

Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.151-171
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• 2023

This study analyzed farmer's responses to the pilot project in advance of the nationwide expansion of the farm-customized early warning service for weather risk management by conducting a survey among all farmers who received text messages of this service. We analyzed not only the satisfaction of farmers with the early warning service, but also the effectiveness of the service in preventing agrometeorological disasters through cross-tabulation analysis of survey results. More than 330 farmers participated in the survey, and more than 60% of the respondents said that they had prevented or mitigated crop disasters by using the early warning service. The cross-tabulation analysis showed that farmers who perceived the field-specific weather information of the early warning service to be more accurate than the weather forecast were statistically significantly more likely to prevent crop disasters than those who did not. According to our case study, farmers who grew open field fruit crops were particularly sensitive to weather information and confirmed that early warning services, along with disaster prevention facilities, were effective in preparing for freezing and frost injury that had been occurring frequently under the influence of climate change. This study is significant in that it is the first to systematically analyze the effectiveness of the farm-customized early warning service for weather risk management based on extensive surveys. It is expected to contribute to exploring ways to develop the service ahead of the nationwide expansion of the early warning service in the near future.

• Research in Plant Disease
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• v.14 no.3
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• pp.193-200
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• 2008

Blending of eggshell powder into soil as ratio of 1:5, 1:10, 1:15, 1:20, and 1:25 did not affect seed germination rates of several crops including Chinese cabbage. The blending increased pH of distilled water and decreased the viability of resting spores of Plasmodiophora hrassicae. The ratio of non-viable resting spores in eggshell-blending water was over five times higher than in distilled water of the same pH. Chinese cabbage (cv. 'Norangbom') grew more in eggshell-blended soil than in non-treated soil, but other crops grew less. Leaf numbers and above ground growth of Norangbom increased to around 150% and 470%, respectively, in soil blended with $1:20{\sim}1:15$ of eggshell powder. Even though the optimum sizes of eggshell powder were $0.8{\sim}2.0mm$ for growth and smaller than 0.4 mm for inhibition of clubroot disease of Chinese cabbage, there was no statistical difference among the sizes. Soil pH was above 8.0 in all eggshell treatments without any statistical difference among them. Eggshell powder blending to 1:20 showed lower control efficacy, 58.5%, than registered fungicide 'Hokanna (flusulfamide)', 78.5%. However, Chinese cabbage of that blending ratio recorded the highest growth among the treatments. Therefore, blending of eggshell powder into clubroot-contaminated soil may make culture of Chinese cabbage possible by growth-increasing, even though eggshell powder could not inhibit clubroot disease entirely.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.1
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• pp.63-72
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• 2009

The experiment was conducted from 2007 to 2008. The experimental roughages include five sources and 25 species in all; grasses and legumes: 5 species (mixed grasses, orchardgrass, tall fescue, alfalfa, white clover), native grasses and weeds: 5 species (mixed native grasses, Miscanthus sinensis Anderss, Arundinella hirta (Thunb.) Tanaka, barnyard grass, short awn, forage crops and straw: 5 species (barley 4- hairy vetch, wheat 4- hairy vetch, rye silage, barley silage, baled rice straw), browse and fallen leaves: 5 species (mixed browse, oriental white oak browse, Quercus serrta Thunb., browse oriental cherry fallen leaves, Japanese chestnut fallen leaves), and imported hay and straw: 5 species (timothy hay, tail fescue straw, annual ryegrass straw, klinegrass hay, alfalfa hay). Ten dairy goats (Saanen) were selected which had nearly the same body weight (25kg). The experiment was carried out on the dairy goats farm at Geumsan-Cun in Chungnam province. The chemical composition and dry matter digestibility of each roughage source and species were significantly different at the sampling area, plant species, growth stages and cutting period. Among all the 25 species of roughages, the favorite intake species order by dairy goats was observed like this: mixed grasses, white clover, alfalfa and the lower intake species order was baled rice straw and rye silages. The dairy goats ate more roughages which had low fibrous contents, but high dry matter digestibility. On the other hand, compared to each roughage source, the goat's favorite roughage were grasses and legumes (34.6%) among the trial species. Based on the result, it is reconfirmed that the food habit of dairy goats seems to be closer to that of graters.

• The Korean Journal of Food And Nutrition
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• v.29 no.3
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• pp.301-306
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• 2016

Vitamin K (phylloquinone) is an essential cofactor in the synthesis of active blood-clotting factors II, VII, IX and X. Deficiency of vitamin K leads to inadequate activity of these factors, resulting in bleeding. In this study, we investigated vitamin $K_1$ content of agricultural products that are widely and specifically grown in Korea including 9 leaves and vegetables, 16 fruits, and 11 cereals and specialty crops. Vitamin $K_1$ analysis of the agro-samples was by a validated, modified, reversed phase-HPLC method with fluorescence detection after post-column derivatization. The vitamin $K_1$ content ranged from 1.83 to $682.73{\mu}g$/100 g in leaves and vegetables, 0.17 to $28.22{\mu}g$/100 g in fruits, and ND to $279{\mu}g$/100 g in cereals and specialty crops. Among the 36 samples, high content of vitamin $K_1$ were found in Gugija (Lycium chinense Miller) leaves (average $682.73{\mu}g$/100 g) and Hansan ramie leaves (average $423.12{\mu}g$/100 g); however, mushroom, amaranth and Chinese artichoke showed no detectable levels. The results of ourstudy provide reliable vitamin $K_1$ content of Korean grown agricultural products that expand nutritional information and food composition database.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.146-157
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• 2019

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.