• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.79-79
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• 2023

With the development of digital technology, the size of the smart agriculture market at home and abroad is rapidly expanding. It is necessary to establish a foundation for sustainable precision agriculture in order to respond to the aging of rural areas and labor shortages. This study was conducted to establish an automated digital agricultural test bed for soybean production management using data suitable for agricultural environmental conditions in Korea and to demonstrate the field of leading complexes. In order to manage water smartly, we installed a subsurface drip irrigation system in the upland field and an underground water level control system in the paddy field. Based on data collected from sensors, water management was controlled by utilizing an integrated control system. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. The main growth characteristics and yield, such as stem length, number of branches, and number of nodes of the main stem, were investigated during the main growth period. During the operation of the test bed, drought appeared during the early vegetative growth period and maturity period, but in the open field smart agriculture test bed, water was automatically supplied, reducing labor by 53% and increasing yield by 2%. A test bed was installed for each field digital farming element technology, and it is planned to verify it once more this year. In the future, we plan to expand the field digital farming technology developed for leading farmers to the field.

• Journal of Agricultural Extension & Community Development
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• v.2 no.2
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• pp.205-227
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• 1995

The objectives of this study were to 1) classify the cooperative farmers' organizations in Korea according to the development level and institutional aspects through the exploration of its' conceptual and institutional basis, 2) analyze the farmers' needs for organization, 3) identify the problems and situation of organizations, and 4) formulate an effective management model for each cooperative farmers' organization. The study was carried out through a review of literature and using available statistical data collected from various sources and empirical survey. Major findings of the study were: 1) the cooperative farmers' organizations could be classified into four types : crop units, farming cooperative corporation, trust farming companies and joint-stock agri-business. 2) a lot of members of the organization feel that the information is insufficient, the opportunity to suggest their own ideas is hardly given, and the members are not satisfied with the cooperation among the members, 3) the members who have higher level of schooling education showed a higher participation level in the organization, 4) most of members did not recognize the organization they participated in, 5) participation of the organization's members and concerned institutions is an important factor to promote problem solving and better communication within the organization, 6) any type of continuing education for the members is needed to facilitate the transfer of a new agricultural and organizational technology, 7) research and development(R & D) is one of the most important factors of the development of organizations, 8) most organizations are deficient in professional management skills(financial, personal, accounts, etc.), 9) the trust farming companies have difficulties in managing the firm on account of the characteristics of agriculture(especially seasonal), the dispersed trust lands, and the need for more alternative work in the winter season, and 10) in the case of agri-businesses, their organizations are more specialized in marketing and have more structured systems of management. Based on the results of the study the following recommendations were made for further improvement and development of agricultural cooperative organizations : (1) More governmental support should be given to education for improvement of the organizational structure. And more deliberate and differentiated governmental support should be provided for the organizations to be viably managed. (2) For more efficient communication between the members and the organization, more opportunities for discussion are needed. (3) The more research should be committed to this kind of work in order to get more analytic data and strategic plans of cooperative organizations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.106-111
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• 2020

In the era of the fourth industrial revolution, the application of big data analysis technology is crucial in various industries. In this regard, considerable research is necessary to improve aquafarming productivity, particularly in fish culture, which is one of the primary industries in the world. In this study, a sample experiment using a flop was conducted to improve oyster productivity in fish farms, and a flush was installed in an environment similar to aquaculture farms. Thereafter, the temperature data of the water environment where the formation of burrows considerably improved were collected; the growth rate of burrow seeds was also measured. The gathered experimental data were examined by time series data analysis. Finally, a system that visualizes the analysis results based on big data is proposed. In accord with the results of this study, it is expected that more advanced research on the productivity improvement of oyster aquafarming will be performed.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.13 no.2
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• pp.45-56
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• 1980

Farming density of oyster cultured in Hansan-Geoje Bay was studied to obtain the optimal farming density based on the biosedimentation analysis and the annual yield data from 1970 to 1979. Farming density of oyster extrapolated by means of pollution grade of sediment is significantly correlated to COD and phaeophytin content of the bottom mud of the bay. Pollution grade is linearly related to the number of oyster clusters suspended in the unit area. Optimal farming density was $0.12\;string/m^2$ in case of raft culture, and it was $0.12\;string/m^2$ in case of long-line culture. Farming density was well expressed by the number of strings per raft and the area covered by a raft. As strings per raft increased from 350 to 558, total yield from a raft increased and when occupied sea area per raft ranged from $1.000\;m^2\;to\;6,000\;m^2$, the yield per raft linearly increased as the area increased. This analysis suggests that the optimal density be 0.11 string per unit area $(m^2)$. As increasing the number of strings per $m^2$ the yield per string decreases, and this is well dipicted by a linear function. At this time the yield per unit area increases when the number of string increases up to the density of $0.13\;strings/m^2$. From the point of these three comprehensive analyses the optimal density was $0.11\~0.13\;string/m^2$ in case of raft culture and $0.25\;strings/m^2$ in case of long-line culture in Hansan-Geoje Bay. The maximum expected yield of oyster in Hansan-Geoje Bay is approximately 5,600 tons when maintained the string density at $0.11\~0.13\;string/m^2$.

• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.65-71
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• 2014

Cacalia firma is a perennial plant in Asteraceae, Parasenecio that distributed in Korea, China, and Japan. As dietary style changes for well-being life, consumer's demand of functional food and organic vegetables is getting increased. This study was conducted to investigate the optimum light conditions of P. firmus in forest farming. One year old seedlings were grown under four different light conditions 10%, 20%, 30%, and 50% of sunlight by shading (equals 50%, 30%, 20%, and 10% relative brightness respectively) and non-treated control under full sunlight. They were analyzed for early growth and physiological response. Seedlings grown under 75% shading showed similar height, root growth, and leaf water content to control. However, their leaf length, width, and total leaf area were increased, which caused increased leaf dry weight and total dry weight. Especially, seedlings under 95% shading showed 40% increase in height and more leaf growth and leaf water content, although they had shorter main root length and root collar diameter than control. In addition specific leaf area (SLA) and leaf area ratio (LAR) were higher than control and indicated that they were statistically significant difference from control. Higher SLA refers thinner leaf thickness, higher LAR means larger leaf area. The results indicate seedlings under 95% shading have higher water content, thinner leaf, and wider lightinterception areas. It is plausible that P. firmus is active in chlorophyll activities and carbon dioxide assimilation at even lower light conditions. These results suggest that the optimum light level of P. firmus for artificial cultivation in forest farming ranges from 75~95% shading (20%-10% of relative brightness). When salability as 'sanchae' (wild edible greens) is considered, P. firmus could be cultivated under 75% shading in forest farming and expected to have better taste and higher yield. We suggest these results as basic data of P. firmus for possible forest farming.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.26-31
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• 2005

In national prospective, the needs to develop water resources has been increased due to water shortage from diverse use of water resources in agricultural areas. Existing agricultural water demand, which has mainly been limited to the use of farming, are now expanding to diverse water uses such as supporting daily lives, diluting environmental pollution as well as industrial use for agricultural complex currently under construction in agricultural region. In this situation, for the sake of effective procurement of water resources and supply method, it is definitely required to enhance the effectiveness of budget investment and project proceedings through integrated re-development which links projects to strengthen existing dams, reservoirs and hydraulic facilities. The major scopes of this research includes developing different types of system such as selecting potential sites to re-construct reservoirs including generating base maps and thematic maps, data collection regarding water demands and reservoir status; analyzing reservoir data; estimating developable capacity and index calculation; and forecasting inundated areas. In addition, this study provides other products such as developing output generation system which can support wide use of data built and analyzed; database generation for better data management; data analysis including selection, extraction, indexation, and calculation of base items through standardization; data security system prohibiting exterior proliferation and malicious manufacturing of data.

• Asia Pacific Journal of Business Review
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• v.1 no.1
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• pp.1-22
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• 2016

The prediction of prices of agricultural products in the agriculture IT sector plays a significant role in the economic life of consumers and anyone engaged in agricultural business, and as these prices fluctuate more often than do other prices, the prediction of these prices holds a great deal of research promise. For this reason, academic literature has provided studies on the factors influencing the prices of agricultural products and the price index. However, as these factors vary, they are difficult to predict, resulting in the challenge of acquiring quantitative data. China is one example of a country without a reliable prediction system for prices of agricultural products. Fortunately, disclosed heterogeneous data can be found on the Internet, which allows for the effective collection of factors related to the prediction of these product prices through the use of text mining. The data provided online is valuable in that they reflect the opinions of the general public in real-time. Accordingly, this study aims to use heterogeneous data from the Internet and suggest a model predicting the prices of agricultural products before functional analyses. Toward this end, data analyses were conducted on the Chinese agricultural products market, one of the largest markets in the world.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.18-28
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• 2002

Neural network based models were developed and evaluated for predicting corn yield from aerial images based on 1998 and 1994 image data. The model used images in multi-spectral bands such as R, G, B, and IR (Red, Green, Blue and Infrared). The inputs to the neural network consisted of mean and standard deviation of multispectral bands of the aerial images. Performances of several neural network architectures using back-propagation with momentum were compared. The maximum yield prediction accuracy obtained was 97.81%. The BPNN model prediction accuracy could be enhanced by using more number of observations to the model, other data transformation techniques, or by performing optical calibration of the aerial image.