• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.27-40
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• 2022

Building self-sustainable rural infrastructure and environment through smart digital agriculture technology innovation is one of the major goals of the Korean agricultural administration as a part of the nation's 4^th industry revolution. To identify areas for improving and effectively investing in the acceleration of rural development, 207 experts in the areas of crop science and smart digital agriculture technology were interviewed for their opinions and suggestions on 22 questions designed to recognize fundamental agricultural issues to be addressed and solutions to advance technology innovation and rural development. Majority of the participants expected smart digital agriculture technologies to resolve major agricultural issues and help build a better rural environment. To overcome technology gaps and resolve issues more effectively, further investment in training new technology experts and building stronger agricultural technology infrastructure is urgent, and persistent and systematic support from agricultural administration appears to be the key for accelerating the process. While the leading global groups of both public and private sectors have advanced their technologies beyond the field application stage, most of the Korean technologies remain at the early pilot stage. Aging population and lack of labor in rural areas, unknown future climate change, and challenges in sustainable rural development are expected to be resolved by smart digital agriculture technologies. Technological innovations by research institutes should be promptly deployed in the crop production field, and farm training systemically organized by local technology centers can accelerate farming revolution. Standardization of equipment and data systems is another key to the success of digitalization of food crop production and food supply chains nationwide.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.171-177
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• 2022

In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.115-126
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• 2019

This study is a survey of people who are return to farming on the intention of accepting ICT convergence technology in agriculture. The research targets were 218 people based on convenience and judgment sampling methods, and the exploratory factor analysis and multiple return analysis were performed with SPSS 22.0. As a result, the independent variables such as performance expectation, effort expectation, and social influence had a positive effect on the acceptance intention of ICT convergence technology in agriculture. In addition, the moderating effects of innovation resistance on these influence relationships were also verified. The limitations of this study are the lack of verification of perception changes and the inability to control variables. As a result of this research, the results of the UTAUT in other fields were confirmed in this study. It is hoped that this study will further facilitate the research of agriculture in ICT convergence technology.

• Research in Plant Disease
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• v.27 no.3
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• pp.120-127
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• 2021

Plant viruses cause significant yield losses, continuously compromising crop production and thus representing a serious threat to global food security. Tomato spotted wilt virus (TSWV) is the most harmful plant virus that mainly infects horticultural crops and has a wide host range. Reverse-transcription quantitative real-time PCR (RT-qPCR) has been widely used for detecting TSWV with high sensitivity, but its application is limited owing to the lack of standardization. Therefore, in this study, a sensitive and accurate reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) method was established for TSWV detection. Additionally, we compared the sensitivities of RT-qPCR and RT-ddPCR for TSWV detection. Specificity analysis of RT-ddPCR for TSWV showed no amplification for main pepper viruses and negative control. TSWV transcripts levels measured by RT-ddPCR and RT-qPCR showed a high degree of linearity; however, the former yielded results that were at least 10-fold more sensitive and detected lower TSWV copy numbers than the latter. Collectively, our findings show that RT-ddPCR provides improved analytical sensitivity and specificity for TSWV detection, making it suitable for identifying low TSWV concentrations in field samples.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.257-259
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• 2005

A crop management system was developed using Visual Basic and ArcGIS VBA. The system is operated on ArcGlS 8.3 with Microsoft Access MOB. Landsat +ETM, KOMPSAT-l EOC, ASTER VNIR and IKONOS panchromatic (pan) and multi-spectral (MIS) images were included in the system to understand what kind of agriculture-related information can be extracted for each images. Agriculture related data inventories using crop cover information such as texture and average pixel value of the crop based on cultivation calendar were designed ,and implemented. Three IKONOS images (May 25,2001, December 25,2001, October 23,2003) were loaded in the system to show crop cover characteristics such as rice, pear, grape, red pepper, garlic, and surface water cover of reservoir with field surveys. GIS layers such as DEM (Digital Elevation Model), stream, road, soil, land use and administration boundary were also supplied and can be overlaid with images to enhance the understanding the general agricultural characteristics and identifying the location easily.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.186-198
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• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2017.11a
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• pp.27-27
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• 2017

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.04a
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• pp.23-23
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• 2022

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.229-238
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• 2022

Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.276-283
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• 2024

Currently, the overall tendency for green and sustainable economic development is creating a circular economy. In actuality, agricultural output is currently benefiting greatly from the growth of the circular economy. The creation of a circular economy helps address resource scarcity, save the environment, combat climate change, and increase economic efficiency. Vietnam's economy can grow quickly and sustainably by shifting to a circular economy production model. Comparing prior growth techniques to the digital age and implementing circular economic development connected with high technology will be a fantastic opportunity to boost growth efficiency. In actuality, Vietnam currently has a large number of agricultural circular economy models. These are models: Creating and using gas from waste and wastewater in livestock and farming; model combining cultivation, livestock, and aquaculture; agro-forestry model; garden-forest model; Circular model using agricultural by-products as a catalyst or creating other valuable products; model of moderation, linked to reducing the use of growth hormones, veterinary medications, pesticides, and artificial fertilizers in agriculture and animal husbandry. Unfortunately, there have been few studies and applications of the aforementioned models, which has made it difficult to build the agricultural sector sustainably. In this paper, we outline the current situation and propose solutions to develop a circular economy model in agriculture in Vietnam for sustainable development.