• Journal of Food Hygiene and Safety
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• 제17권3호
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• pp.146-151
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• 2002

The contents [average(minimum∼maximum), Unit:mg/kg] of hazardous heavy metals(Hg, Cd and Pb) were estimated from 951 fishery products in Seoul(468 fishes,373 shellfishes, 39 crustaceans and 71 others) from January to December in 2001 by Atomic Absorption Spectrometer. Hg contents showed in shellfishes [0.033(N.D.∼0.19)]>others(0.026(N.D.∼0.11)]>crustaceans[0.026(N.D.∼0.09)]>fishes[0.018(N.D.∼0.19)], Misgurnus mizolepis(0.19) and Tegillarca granosa(0.19) were the highest. Pb content were shellfishes [0.223(N.D.∼l.38)] >fishes[0.213(N.D.∼1.68)]>others[0.15(N.D.∼0.39)]>crustaceans[0.144(N.D.∼0.444)], and Misgurnus mizolepis (1.68)>Hypomesus olidus(1.44)>Tapes philippinarum(1.38)>Anguilla japonica(1.35). Also, Tegillarca granosa(1.85) was the most Cd contents among shellfishes[0.288(N.D.∼1.85)].

• Food Science and Industry
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• 제54권4호
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• pp.293-300
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• 2021

Food safety accidents have been increasing by 2% over 5,000 cases every year since 2009. Most people know that the best method to prevent food safety accidents is a quick inspection, but there is a lack of inspection technology that can be used at the non-analytic level to food production and distribution sites. Among the recent on-site diagnostic technologies, the methods for testing gene-based food poisoning bacteria were introduced with the STA technology, which can range from sample to detection. If food safety information can be generated without forgery by directly inspecting food hazard factors by remote, unmanned, not human, pollution sources can be managed by predicting risks more accurately from current big-data and artificial intelligence technology. Since this information processing can be used on smartphones using the current cloud technology, it is judged that it can be used for food safety to small food businesses or catering services.

• International Commerce and Information Review
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• 제13권1호
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• pp.29-52
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• 2011

A predictable and manageable output is desirable for most businesses. However, it is very difficult to control the quality and quantity of products in the food and agriculture business. Predictable outputs help managers plan their marketing, sales, and inbound and outbound logistics, but these are not easy to achieve in the food and agriculture business. Various industries have adopted different levels of automation and utilization of information systems for quality/quantity control; however e-Commerce of the food and agriculture industry is far behind those of other industries. Today, the food and agriculture industry is supposed to be more integrated than ever in order to reduce risks and improve processing costs, from farm to table. Since its operations including production, processing, storage, distribution, and management are dispersed all over the world, the food and agricultural industries now depend more on IT than other industries. This study attempts to develop a framework to analyze the current situation of agricultural product e-Commerce in Korea, and finds out the actual situation of the farmers operating on-line shopping systems through the developed framework and suggests some improvements.

• The Korean Journal of Applied Statistics
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• 제33권2호
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• pp.215-228
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• 2020

Under Article 19, Paragraph 1 of the Food Industry Promotion Act, Rural Development Administration renews the Korean foods composition table every five years. Before the publication of the tenth revision of the Korean foods composition table in 2021, this paper suggests methods for collecting representative samples of 182 highly consumed foods in Korea. Food markets are categorized by their distribution channels, which are supermarkets and local markets. Eight samples are collected from each category by applying the National Food and Nutrient Analysis Program (NFNAP)'s stratified multi-stage sampling. The NFNAP was implemented in 1997 as a collaborative food composition research effort between the National Institute of Health (NIH) and the US Department of Agriculture (USDA) to secure reliable estimates for the nutrient content of food and beverages consumed by the US population. Selected supermarkets for selecting representative food samples are Emart Kayang, Homeplus Siheung, Lottemart Dongducheon, Emart Suwon, Lottemart Dunsan, Lottemart Yeosu, Emart Ulsan, and Hanaroclub Ulsan. Selected local markets also are Doksandongusijang in Geumcheon-gu and Pungnapsijang in Songpa-gu, Seoul, Ilsansijang in Ilsanseo-gu, Goyang, Unamsijang in Buk-gu, Gwangju, Beopdongsijang in Daedeok-gu, Daejeon, Bongnaesijang in Yeongdo-gu and Jwadongjaeraesijang in Haeundae-gu, Busan, and Jungangsijang in Jinhae-gu, Changwon.

• Korean Journal of Agricultural Science
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• 제32권2호
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• pp.215-221
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• 2005

The residual study of pesticide has been used in various areas, such as food safety, environmental protection, establishment of tolerance, and explaining the pathway and reaction mode of pesticides, and its importance was expected to increase further more. The aspect of food safety, the pesticide residue survey have been practiced at many organizations, but there were no verification of analytical results at present. In this experiment, we focused on instrumental stability, including response of each instrument and the recovery ratio of each organization's method. As samples for this experiment, we prepared cucumber and sesame, and chose 4 pesticides (bifenthrin, chlorpyrifos, diazinon, and ethoprophos), which were mostly detected from pesticide residue survey and widely used for each crop. The standard deviation of peak areas in the chromatogram of each pesticide were under 1.212 %, so it showed that most instruments were stable. The relationship of recovery ratio of each organization were over 0.996 for every pesticide and each organization. Finally, the analytical results for pesticide residue from each participated organization were not statically significant and we could put confidence in the result from each organization.

• Korean Journal of Food Science and Technology
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• 제38권4호
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• pp.594-598
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• 2006

The aim of this study was to investigate the prevalence and frequency of food-borne pathogens in unprocessed Products such as grains, tubers, vegetables, and seaweeds. Three hundred and twenty seven samples were purchased from the retail market and the supermarket in the Kyonggi-do and Seoul areas, and washed with running tap water for 4 minutes. The total aerobic bacteria count was approximately 2 to 6 log CFU/g and the highest counts were 6 log CFU/g far lettuce and sesame leaf. The coliform count showed 1-5 log CFU/g and the highest counts were 4 log CFU/g for lettuce and carrot. Escherichia coli was detected in seven samples of white rice, sweet potato, lettuce, sesame leaf, and cabbage. Clostridium perfringens was detected in six samples of brown seaweed, laver, lettuce, and sweet potato. However, Bacillus cereus contamination was found in more than 30% of brown rice, carrot, sweet potato, lettuce and sesame leaf samples, and some of these showed contamination of more than 2.0 log CFU/g. Therefore, these results suggest that pretreatment with sanitizer to remove Bacillus cereus in such products is necessary.

• The Korean Journal of Pesticide Science
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• 제14권4호
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• pp.381-393
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• 2010

In order to monitor the residual characteristics of the pesticides in leafy vegetables selling at wholesale markets and traditional markets in Cheongju, a total of 180 samples of 15 leafy vegetables, such as broccoli, celery, chard, chicory, Chinese vegetable, Chwinamul, crown daisy, Korean cabbage, leek, lettuce, perilla leaves, Shinsuncho, spinach, welsh onion and young radish, were purchased from the wholesale markets and traditional markets in June and August in 2010 and the pesticide residues in them were analyzed by multiresidue analysis method using GLC, HPLC and GC-MSD. Seven pesticides were detected from 12 samples out of total 180 samples collected, representing detection rate was 6.7%. In case of the samples collected from markets in June, four pesticides including tefluthrin were detected from six samples and in case of the samples collected from markets in August, three pesticides including pendimethalin were detected from three samples. The MRL-exceeding rate of pesticides detected from leafy vegetables was 0.6%. The pesticide exceeded its MRL was azoxystrobin detected from crown daisy and many pesticides were not registered to the crops, excepting that azoxystrobin detected from Chwinamul and tefluthrin from leek. Estimated daily intakes (EDIs) of the pesticides detected from leafy vegetables were less than 7% of their acceptable daily intakes (ADIs), representing that residue levels of the pesticides detected were evaluated as safe.

• Journal of Intelligence and Information Systems
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• 제20권3호
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Digital Convergence
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• 제20권4호
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Journal of Practical Agriculture & Fisheries Research
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• 제20권2호
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• pp.57-72
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• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.