• The Ewha Medical Journal
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• v.40 no.3
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• pp.99-103
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• 2017

Antimicrobials were one of the great invention of modern era. However, the abuse of antimicrobial both in human and animals has led to a high rate of occurrence of antimicrobial resistant microbes. Disease treatment caused by antimicrobial resistant microbes including superbacteria has emerged as critical issue worldwide. Communication and cooperation among researchers in diverse fields are needed to solve the resistance to antimicrobials. Culture Collection of Antimicrobial Resistant Microbes (CCARM) has taken a leadership role an intermediary among various research fields by providing certified antimicrobial resistant microbes with their information since 1999. CCARM collects antimicrobial resistant microbes from clinical, agricultural animals and products, and environmental fields, and classifies and stores them according to their origins, species and antimicrobial resistance mechanisms. CCARM is performing the roles (collection, deposit, preservation, distribution, service, and consulting) of Biological Resource Center designated by Organisation for Economic Co-operation and Development.

• The Korean Journal of Food & Health Convergence
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• v.9 no.2
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• pp.7-18
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• 2023

Through these research results, I would like to present some implications for promoting and revitalizing local food sales in Daejeon and establishing a local food system. First, in terms of local food direct stores, when establishing a local food store, location conditions should be considered. If the location cannot be changed, the quality of agricultural products should be improved to improve consumer satisfaction and purchase intention so that consumers can directly feel the value of the product. Second, efforts at the local government level are needed to improve the stability of local food. There are still many consumers who are not properly aware of local food. It is necessary to improve consumers' interest in the value of local food by providing education including social and environmental information on the production and distribution process of local food. Third, policy efforts on local food are needed. It is necessary to introduce and reorganize the local food certification system to emphasize the stability of local food to consumers and form trust. Finally, for the continuous development of local food, research on the satisfaction and purchase intention of local food consumers must be continuously conducted.

• Journal of Distribution Science
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• v.16 no.1
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• pp.87-99
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• 2018

Purpose - The Export Infrastructure Strengthening Program(EISP) is a project to expand exports of agri-food products through providing customized export information to food distribution companies and supporting overseas information activities. A total of 39.6 billion won was provided by 2016. So, the purpose of this study is to analyze whether EISP is effective for expanding exports of agri-food products. Research design, data, and methodology - A simple average difference between the export performance of the policy beneficiaries and the non-policy beneficiaries can be biased if the export capacity or inherent characteristics of the enterprise are not taken into consideration. In order to solve the problem of such a bias, the propensity score matching(PSM) method has been employed in this study. PSM is a method of converting the characteristics of an export company into an index through logit analysis and then reducing the matching to one dimension to improve the accuracy of the performance measurement. Results - The balancing test was conducted to determine how the characteristics of the policy beneficiary group and the matched policy non-beneficiary group corresponded to each other. As a result of the test, we could not reject the null hypothesis that there was no difference between the two groups, so that after the matching, the two groups were similar and the explanatory variables were well controlled. Using the nearest neighbor matching with propensity score estimating through logit analysis, we estimated average treatment effect on the treated(ATT). The food companies participating the EISP had the effect of increasing the exports of $ 5.88 million. As a result, the number of export contracts increased by 11.77, the number of exporting countries by 7.52, the number of export items by 47.51, and the number of buyers' consultation by 3.50. And overseas marketing expenses increased by 35.92 million won. Except for the number of export contracts, other export performance results showed statistically significant results. Conclusions - As the EISP has a positive effect on the expansion of agro-food exports, efforts should be made to find out the limitations or problems of the policy in the future and to make a greater contribution to the increase of exports.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1540-1549
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• 2017

Objective: Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods: We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results: We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion: The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.

• Journal of Agricultural Extension & Community Development
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• v.19 no.4
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• pp.961-987
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• 2012

The present study is to investigate the characteristics and determinants of spatial distribution of strong small farm by defining the term, strong small farm (SSF) extracting the SSF households data dealing with apples, from 2010 Census of Agriculture, Forestry and Fisheries, Korea. Spatial distribution and concentration of SSF are analyzed based on spatial clustering techniques. We construct discrete dependent variables on strong and non-strong small farms and then analyze the determinants of the SSFs using probit model, with independent variables including population and economic characteristics and management characteristics. As of 2010, the apple SSFs, 1,529 households in total, are geographically concentrated in Gyeonsangbuk-do according to the analysis results. The determinants of SSF are similar to those of farms' earnings. When located in the apple producing area, and participating in producers organization while selling products directly, the farm is highly likely an SSF. The findings and results of the present study are expected to provide fundamental information helpful for preparing and implementing policies for SSFs in that the present study investigates the characteristics of SSF, which is a prerequisite step for SSF-related policies.

• Journal of Korean Society of Rural Planning
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• v.26 no.2
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• pp.117-126
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• 2020

In this study, demands of smart technology development were analyzed for rural village communities. Questionnaire items were derived by grasping the current status of information and communication technology. 49 villages in 8 regions were selected and surveys and statistical analysis were conducted. The main results of the study are as follows. First, 92% of community leaders use smartphones, search for information (38%), communicate with the Internet (36%) using smartphones, use KakaoTalk (31%), and Facebook (24%). Second, in the rural and urban exchange activities, promote support information service (51%) and promote method suggestion service (48.5%) showed that the demand for services in promote field was high. It is linked to the creation of economic opportunities. Third, in the income and production activities, demand for distribution services technology (39.3%) was high in the field of production and distribution, and cold chains that help maintain freshness until food, such as meat, fish, and vegetables are delivered to consumers when agricultural products are distributed. The constant temperature control system needs to be actively introduced. Fourth, autonomy activities showed the highest demand for air conditioning and control systems (34.2%) of community building, and the lowest demand for electronic voting (9.4%) and videoconferencing (9.4%) services. Lastly, in the general activity area of the community, the demand for technology of emergency services (37.1%) and health self-diagnosis service (35.4%), which are technologies in the welfare sector, ranked first and second respectively.

• Agribusiness and Information Management
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• v.2 no.1
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• pp.15-29
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• 2010

Recently, IPTV population is growing by leaps and bounds. and We performed FGI(Focus Group Interview) with various experts related to agriculture field to establish Agriculture and Fisheries special channel. this growth has social background that is change of paradigm caused by the convergence of broadcasting, demand for Agriculture and Fisheries special channel using new media thanks to interests in Wellbeing, Green food. so we think that we need to consider the way to establish Agriculture and Fisheries special channel and its validity from all angles. that is why we are having a heated discussion with Agriculture and Fisheries marketing experts, farmer, fisher(Korean Cyber Farmer Association), broadcasting experts. Concretely, government budget is needed to establish Agriculture and Fisheries special channel, so we are just about to examine its validity and find business model. to make this discussion detailed, we made 4 subjects. First, Do we need agro-fishery products distribution channel using media? Second, After establishing of Agriculture and Fisheries special channel, how many demands will occur? Third, Should we make Agriculture and Fisheries special channel public channel? Fourth, What would be profit model of Agriculture and Fisheries special channel?

• Korean Journal of Environment and Ecology
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• v.33 no.6
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• pp.654-663
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• 2019

Pollinators, which are important organisms in pollination ecology, have been highly valued for their economic contributions to crop production in the agricultural and biotechnology industries. As the production of over 70% of farm products, such as fruits, are mediated by pollinators, bees are important and useful insects to humans. However, pollinators are now seriously threatened with their numbers decreasing annually and their biodiversity being negatively affected by ongoing climate change, misuse of land, change of geographical features, and use of pesticides to increase agricultural production. Thus, surveys and analyses of the emergence and distribution of wild bees are important for conservation and management practices designed to help them continue to play their ecological and agricultural roles despite negative pressures, such as climate and topography changes. We surveyed pollinators, especially wild bees, at 51 research sites in South Korea every two to four weeks for two years from 2017 to 2018 using ez-Malaise traps and analyzed the temporal and spatial distribution of wild bees. The bees showed a normal temporal distribution that peaked between July and August. The bees' working period lasted until November. The spatial distribution of wild bees showed a significant correlation with latitude, and different bees were identified depending on the local habitat. No significant correlation was found for longitudinal distribution with regression analysis (p > 0.05), but this study identified locally specific wild bees. Although we could not predict significant distribution according to longitude, Further studies should be able to analyze the difference in the distribution of wild bees according to the climate, topography, and land-use patterns by humans. The results of this study provide basic information on pollinator distribution, which can be useful in agriculture and for the conservation and management of biodiversity in South Korean pollination ecology.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.7
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• pp.1202-1208
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• 2020

Objective: The aim of this study was to identify a distribution pattern of meat quality grade (MQG) as a function of carcass yield index (CYI) and the gender of Hanwoo (bull, cow, and steer) to determine the optimum point between both yield and quality. We also attempted to identify how pre- and post-deboning variables affect the gender-specific beef quality of Hanwoo. Methods: A total of 31 deboning variables, consisting of 7 pre-deboning and 24 post-deboning variables from bulls (n = 139), cows (n = 69), and steers (n = 153), were obtained from the National Institute of Animal Science (NIAS) in South Korea. The database was reconstructed to be suitable for a statistical significance test between the CYI and the MQG as well as classification of meat quality. Discriminant function analysis was used for classifying MQG using the deboning parameters of Hanwoo by gender. Results: The means of CYI according to 1+, 1, 2, and 3 of MQG were 68.64±2.02, 68.85±1.94, 68.62±5.88, and 70.99±3.32, respectively. High carcass yield correlated with low-quality grade, while high-quality meat most frequently was obtained from steers. The classification ability of pre-deboning parameters was higher than that of post-deboning parameters. Moisture and the shear force were the common significant parameters in all discriminant functions having a classification accuracy of 80.6%, 71%, and 56.9% for the bull, cow, and steer, respectively. Conclusion: This study provides basic information for predicting the meat quality by gender using pre-deboning variables consistent with the actual grading index.