• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.681-682
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• 2018

There are many damages due to the unstable climate. Among them, agriculture will be the most affected by the climate. Agriculture has limited crops that can be grown along with climate and seasons. We will develop smart farms that integrate information technology(ICT) into agricultural technology and improve the productivity of existing agricultural technology. It uses Raspberry Pi and Arduino to control the hardware and software, and uses various sensors to recognize the environment necessary for crop cultivation and maintain optimal environment. In addition, it is possible to manipulate these Smart Farm as mobile or personal PC to implement a flexible Smart Farm.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• Mycobiology
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• v.50 no.1
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• pp.79-85
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• 2022

Strawberries are a popular economic crop, and one of the major plantations and exporting countries is Korea in the world. The Fusarium oxysporum species complex (FOSC) is a soil-borne pathogen with genetic diversity, resulting in wilt disease in various crops. In Korea, strawberries wilt disease was first reported in the 1980s due to the infection of FOSC, causing significant economic damage every year. The causal agent, F. oxysporum f. sp. fragariae, is a soil-borne pathogen with a characteristic of FOSC that is difficult to control chemically and mutates easily. This study obtained genetic polymorphism information that was based on AFLP, of F. oxysporum f. sp. fragariae 91 strains, which were isolated from strawberry cultivation sites in Gyeongsangnam-do and Chungcheongnam-do, and compared strains information, which was the isolated location, host variety, response to chemical fungicide, and antagonistic bacteria, and mycelium phenotype. As a result, AFLP phylogeny found that two groups were mainly present, and group B was present at a high frequency in Gyeongsangnam-do. Group B proved less sensitive to tebuconazole than group A through Student's t-test. In addition, the fractions pattern of AFLP was calculated by comparing the strain information using PCA and PERMANOVA, and the main criteria were separated localization and strawberry varieties (PERMANOVA; p< 0.05). And tebuconazole was different with weak confidence (PERMANOVA; p< 0.10). This study suggests that the F. oxysporum f. sp. fragariae should be continuously monitored and managed, including group B, which is less chemically effective.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.283-284
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• 2021

The domestic and overseas IoT (Internet of Things)-based automation industry is developing remarkably, and the development of this automation technology is further accelerated by the development of sensor technology. In recent years, the smart farm industry for the purpose of growing crops based on various sensor technologies is rapidly developing. In the case of smart farms, real-time monitoring and mobile services are provided by measuring representative environmental data such as temperature, humidity, and CO2 required for crop cultivation. Most of these environmental monitoring and control operations use the RS-485-based Modbus (RTU) communication method. In this paper, we intend to test the performance of sensor data and actuator information required for smart farm construction by building a platform for controlling sensor data and actuators based on LabView using MQTT (Message Queuing Telemetry Transport), an IoT standard protocol.

• Smart Media Journal
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• v.12 no.10
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• pp.29-37
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• 2023

Human lifestyle is affected by the agricultural development in the last 12,000 years ago. The development of agriculture is one of the reasons that global population surged. To ensure sufficient food production for supporting human life, pesticides as a more effective and economical tools, are extensively used to enhance the yield quality and boost crop production. This study investigated the factors that affect crop production and whether the factors of pesticide usage are the most important factors in crop production using the dataset from Kaggle that provides information based on crops harvested by various farmers. Logistic regression is used to investigate the relationship between various factors and crop production. However, the logistic regression is unable to deal with predictors that are related to each other and identifying the greatest impact factor. Therefore, causal discovery is applied to address the above limitations. The result of causal discovery showed that crop condition is greatly impacted by the estimated insects count, where estimated insects count is affected by the factors of pesticide usage. This study enhances our understanding of the influence of pesticide usage on crop production and contributes to the progress of agricultural practices.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.180-194
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• 2017

Agricultural hazards management technology, which would allow individual farms to respond preemptively, has been developed. A preliminary system developed in the previous study provides precise weather forecasts by farms, notification of weather hazards by crops and delivery of response guidelines (http://www.agmet.kr). Although the GIS map-based alarm system has been implemented for a number of farmers and their farms, its user interface was not designed for individual users who seek information at their farms. In this study, we have developed a mobile application to provide early warnings of weather hazards up to 10 days in advance. A set of information including field-specific weather, crop growth stages and weather hazard alerts can be delivered to individual farmers through their mobile phone. This would guide users to access the map-based system using their smartphone to obtain field-specific weather information by the growth stage of cultivated crops. This would help the farmers make the better use of the existing weather-hazard GIS map-based alarm system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.764-769
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• 2000

A new transplant production system that produces high quality plug seedlings of specific crop has been studied. It is a plant factory designed to produce massive amount of virus free seedlings. The design concept for building this plant factory is to realize maximum energy efficiency and minimum initial investment and running cost. The basic production strategy is the sitespecific management. In this case, the management of the growth of individual plantlet is considered. This requires highly automated and information intensive production system in a closed aseptic environment the sterilized specific crops. One of the key components of this sophisticated system is the irrigation system. The conditions that this irrigation system has to satisfy are: 1. to perform the site specific crop management in irrigation and 2. to meet the no waste standard. The objective of this study is to develop an irrigation scheduling that can implement the no waste standard.

• Journal of Agricultural Extension & Community Development
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• v.8 no.2
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• pp.245-261
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• 2001

The consulting industry had enjoyed growth rates over the past 20 years which show no signs of slowing in their momentum. Since 1995, it began to discuss institutionalization of consulting in the agricultural sector in Korea. Rural Development Adminstration has launched farm management consulting project by means of benchmarking for farming innovation in 1988, which consists of establishing consulting team, developing standard diagnosis form of sixty crops and materials, training consultants, having various public relations, and making information systems. Until October, 2001, sixty seven thousands of farmers have benefited on this project. It is now appreciated as a alternative for new agricultural extension approach. Analyzing the changes of farm management practice level through consulting shows improvement, which data have been stored in web database. It is expected that farm management consulting project be main stream of agricultural extension in this country.