• Information Systems Review
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• v.22 no.1
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• pp.113-124
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• 2020

In the operation of farms, it is very important to evaluate the quality of harvested crops and to classify defective products. However, farmers have difficulty coping with the cost and time required for quality assessment due to insufficient capital and manpower. This study thus aims to detect defects by analyzing the epidermis of fruit using deep learning algorithm. We developed a model that can analyze the epidermis by applying YOLOv3 algorithm based on Region Convolutional Neural Network to video images of peach. A total of four classes were selected and trained. Through 97,600 epochs, a high performance detection model was obtained. The crop failure detection model proposed in this study can be used to automate the process of data collection, quality evaluation through analyzed data, and defect detection. In particular, we have developed an analytical model for peach, which is the most vulnerable to external wounds among crops, so it is expected to be applicable to other crops in farming.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.403-417
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Journal of Mushroom
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• v.15 no.3
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• pp.118-123
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• 2017

This study was carried out to develop the technology to manage the growth of mushrooms, which were cultivated based on long-term information obtained from quantified data. In this study, hardware that monitored and controlled the growth environment of the mushroom cultivation house was developed. An algorithm was also developed to grow mushrooms automatically. Environmental management for the growth of mushrooms was carried out using cultivation sites, computers, and smart phones. To manage the environment of the mushroom cultivation house, the environmental management data from farmers cultivating the highest quality mushrooms in Korea were collected and a growth management database was created. On the basis of the database value, the management environment for the test cultivar (hukthali) was controlled at $0.5^{\circ}C$ with 3-7% relative humidity and 10% carbon dioxide concentration. As a result, it was possible to produce mushrooms that were almost similar to those cultivated in farms with the best available technology.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.141-148
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• 2021

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. It is expected that agrivoltaic systems can realize climate smart agriculture by reducing evapotranspiration and methane emission due to the reduction of incident solar radiation and the consequent surface cooling effect and bring additional income to farms through solar power generation. In this study, to evaluate that agrivoltaic systems are suitable for realization of climate smart agriculture, we conducted agro-environmental observations (i.e., downward/upward shortwave/longwave radiations, air temperature, relative humidity, water temperature, soil temperature, and wind speed) in a rice paddy under an agrivoltaic system and compared with the environment outside the system using automated meteorological observing systems (AMOS). During the observation period, the spatially averaged incoming solar radiation under the agrivoltaic system was about 70% of that in the open paddy field, and clear differences in the soil and water temperatures between the paddy field under the agrivoltaic system and the open paddy field were confirmed, although the air temperatures were similar. It is required in the near future to confirm whether such environmental differences lead to a reduction in water consumption and greenhouse gas emissions by flux measurements.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.25-48
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• 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 the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.192-207
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• 2020

Profitability of upland crops is better than paddy crops and proportion of upland is increasing. However, there is a lack of infrastructures for upland irrigation. The object of this study were to develop water supply scenarios using individual and collective agricultural wells to evaluate economic feasibility to consider geographical analysis of upland farms and water supply facilities. Cheongyang, Dangjin, Yesan, and Goesan were selected as study areas where four different crops of red pepper, chinese cabbage, apple, and bean, respectively, were mainly produced in Chungcheong province. As a result, B/C ratio was estimated as 1.49, 1.36, 1.90, and 0.71 in using individual wells scenario, and 1.45, 1.20, 1.91, and 0.65 in using collective wells scenario for red pepper, chinese cabbage, apple, and bean. It turned out that change of price effected on economic feasibility a lot for crops with low production income. As a result of evaluating economic feasibility by number of plots for developing collective well, there was no effect of economy of scale for red pepper and chinese cabbage. In case of collectivizating more than 20 upland plots, effect of economy of scale appeared for apple and bean. In conclusion, development of water using high value crops including red pepper and apple, and effect of collective well requires additory analysis of .spatial distribution of farms.

• Journal of Bio-Environment Control
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• v.27 no.2
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• pp.147-157
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• 2018

With the rapid development of the 4th industrial revolution, the large-sized facilities of agriculture have been developed with high-technologies. However, it is difficult to maintain the optimum environment in large-sized facilities. Although it is essential to control micro-climate properly in large-sized facilities, there are a lot of problems to utilize high-technologies and equipment because of insufficient education for farmers. Most farms have limitations to access to their farm because of prevention of epidemics, exposure of management know-how, and so on. Especially, it is difficult to understand internal environmental factors (airflow, temperature, humidity, etc.) for farmers because these factors are invisible. Recently, Virtual reality technology which allows users to experience various phenomena directly is attracting attention. Virtual reality is very useful technology to visualize airflow and temperature distribution and so on. However, there is no cases applied this technology to agricultural facilities. In this study, research trends of virtual reality in various fields were investigated. In particular, the limitation and possibility of virtual reality technology were analyzed for educating farmers. Finally, the development of virtual reality contents for smart-farm facility were suggested.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.320-331
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• 2013

The National Center for AgroMeteorology (NCAM) has designed a risk management solution for individual farms threatened by the climate change and variability. The new service produces weather risk indices tailored to the crop species and phenology by using site-specific weather forecasts and analysis derived from digital products of the Korea Meteorological Administration (KMA). If the risk is high enough to cause any damage to the crops, agrometeorological warnings or watches are delivered to the growers' cellular phones with relevant countermeasures to help protect their crops against the potential damage. Core techniques such as scaling down of weather data to individual farm level and the crop specific risk assessment for operational service were developed and integrated into a cloud based service system. The system was employed and implemented in a rural catchment of 50 $km^2$ with diverse agricultural activities and 230 volunteer farmers are participating in this project to get the user-specific weather information from and to feed their evaluations back to NCAM. The experience obtained through this project will be useful in planning and developing the nation-wide early warning service in agricultural sector exposed to the climate and weather extremes under climate change and climate variability.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.137-141
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• 2012

The foot and mouth disease(FMD) was occurred from Andong city on November 23, 2010 and spread out the whole country except Jeju island and Jeolla-do. About 3.4 million livestock such as cow and pig was buired at 4,200 sites during preventive measures of FMD. Government did not effectively respond to the FMD crisis management so FMD spread out the whole country. To Prevent the spread FMD, Farms have to fast approaching and respond directly to smartphones and Tablet PC applications. Resolve the difficulties of using smart devices and easy to operate for the effective utilization of the development of simple applications. This application of FMD, developed for the prevention and alarm applications, foot and mouth disease will be caused, farmers around the farm in case of risk and the seriousness of the FMD will notify smartphone, FMD prevent additional damage due to be interested in preventing further that allows your application is for development purposes.