For the analysis of hazard factors and the development of GAP (Good Agricultural Practices) Ginseng, 10 ginseng cultural farms wished certified GAP were selected at Geumsan-gun area, a representative site of ginseng cultivation in Korea. In order to verify the safety of GAP ginseng, possible contamination of pesticide and heavy metal residues, and microbial hazard were analyzed. Soil and water around ginseng cultivation field, and ginseng were investigated. Eighty-one pesticides including carbendazim were used as typical pesticide against plant pathogens and insect pests of ginseng plant and general crops. There was no excess the maximum residue limit (MRL) in residue figure of the soil. Including the residue figure of the arsenic (0.81 ml/kg) and 7 other heavy metals was also suitable to cultivate the ginseng plant. The irrigation water and dilution water for pesticide application were also safety level for GAP. Fresh ginsengs from the farms were sampled and investigated pesticide residues and contaminations of bacteria. Among 23 pesticides tested, we didn't detect any kinds of pesticide residues, but tolclofos-methyl was frequently found in the other ginseng field. On the investigation of microorganism hazards, 2 gram negative bacteria and 1 gram positive bacterium were found in the fresh ginseng. Number of total bacteria was $1.5{\times}10^3$ cfu/ml, which was less than the other agriculture products. At these results, 10 selected ginseng farms were good cultural places for GAP ginseng production and the ginseng cultured from Geumsan-gun area were a good safe far human.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.11
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pp.532-542
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2020
Due to abnormal weather conditions such as high temperature, the management of greenhouse rose farms is getting worse. In order to enhance the competitiveness of these farms, new measures are needed to improve their management performance. Therefore, this study suggests alternatives to improve the efficiency and productivity by identifying the causes of inefficiency of greenhouse rose farms in terms of management performance analysis through DEA analysis and MPI analysis. As a result of DEA analysis, the average TE of farmers increased from 0.867('16) to 0.905('17), but decreased to 0.850 in 2018, indicating that it was inefficient. In order to increase the management efficiency of farmers, efforts to preferentially reduce the costs (equipment, employment labor, fertilizer, facilities, seeds) that cause inefficiencies are needed. As a result of MPI analysis, TECI decreased from 1.044(T2) to 0.939(T3), which was the cause of the MPI decrease, and the TCI was rather increased from 0.958(T2) to 0.969(T3). In other words, it means that the decrease in productivity is due to insufficient utilization of potential production technology rather than the slowing of technological progress. This implies that it is important to provide technical guidance on utilization after technology dissemination.
A random study of 574 dairy farms in Gyeongnam area was designed to determine 1) management factors that may be associated with the occurrence of drug residues; 2) the dairy farmer's attitudes and knowledge about residues; 3) how these variables influence the occurrence of residues in dairy cattle. Management factors perceived as having the greatest influence on drug residues in milk were insufficient knowledge about withdrawal periods, errors due to hired help, insufficient identification and record of animals treated for mastitis, dry cow treatment for mastitis, and metritis treatment. Seventy-one percent of farms with residues problem used mixed own feeds compared with twenty-nine percent of farms with premedicated feeds. Factors significantly associated with the occurrence of residues were herd size, increased number of hired persons, increased frequency of use of mixed-own feeds, category of medicated feed, and producer's attitude toward the public health significance of residues. Our findings suggest that residue occurrence was mainly associated with errors due to hired help, insufficient knowledge about withdrawal periods, poor animal identification and records of treatment animals and use of medicated feeds. Any residue avodiance educational program needs to stress how to deal with these factors. This educational program should be directed to dairy farmers and employees, especially temporary employees. In addition, Dairy farmer's attitudes and knowledge about drug residues need to be improved. More evidence on the public healths significance of residues should be available to them. Because belife in importance of public healths concerns was related to successful residue avidance and because 81.3% of the dairy farmers with residue problem thought public healths concerns were less important than economic ones, it would be helpful to provide educational programs specifically directed to this issue. it may be useful to provide programs not only for the dairy farmers but also change of their concerns about on the public healths.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.12
no.6
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pp.672-680
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2019
This paper proposes "A Smart Farm Environment Optimization and Yield Prediction Platform based on IoT and Deep Learning" which gathers bio-sensor data from farms, diagnoses the diseases of growing crops, and predicts the year's harvest. The platform collects all the information currently available such as weather and soil microbes, optimizes the farm environment so that the crops can grow well, diagnoses the crop's diseases by using the leaves of the crops being grown on the farm, and predicts this year's harvest by using all the information on the farm. The result shows that the average accuracy of the AEOM is about 15% higher than that of the RF and about 8% higher than the GBD. Although data increases, the accuracy is reduced less than that of the RF or GBD. The linear regression shows that the slope of accuracy is -3.641E-4 for the ReLU, -4.0710E-4 for the Sigmoid, and -7.4534E-4 for the step function. Therefore, as the amount of test data increases, the ReLU is more accurate than the other two activation functions. This paper is a platform for managing the entire farm and, if introduced to actual farms, will greatly contribute to the development of smart farms in Korea.
Offshore wind power is a representative renewable energy source and a rapidly growing industry. In Gyeongsangnam-do, offshore wind farms of 461.9MW are being pushed for in the Yokji island and are expected to expand further to over 1GW in the future. Accordingly, ports supporting the storage, assembly, transportation, and installation of offshore wind power equipment are expected to play an important role in the smooth progress of the offshore wind farm development project. Based on previous research and cases in major countries,this study prepared criteria for assessment of ports supporting offshore wind farmsand evaluated ports in Gyeongsangnam-do, which are linked to Yokji island offshore wind farms. The assessment criteria have been subdivided into distance from the offshore wind farm, port entry and exit restrictions, navigational areas, fishery rights factors, additional costs, berth length, depth of berth, size of the port yard, port berth bearing pressure, interference with other cargo, a civil appeal, and relevant industrial aggregation. The ports of Tongyeong, Samcheonpo, Kohyun, Masan, and Jinhae in Gyeongsangnam-do were selected and evaluated. As a result, the port of Tongyoung was superior in terms of distance from the Yokji island offshore wind farm. The ports of Samcheonpo, Masan, and Jinhae were evaluated as excellent in other criteria such as berth length, depth of berth, and so on. This study is expected to be used as a source of basic data for offshore wind power companies and policymakers to select and evaluate the supporting ports of offshore wind farms.
The offshore wind farm is increasingly attractive as one of future energy sources all over the world. In addition, the capacity of an offshore wind turbine gets larger and its physical characteristics are big and heavy. In this regard, a special port is necessary to assemble, store, and transport the offshore wind systems, supporting to form the offshore wind farms. Thus, this study aims to provide a policy maker which evaluation factors can significantly affect to the optimal site selection of a offshore wind port. For this, Fuzzy-AHP method is applied to capture the relative weights. The results of this study can be summarized as follows. Five criteria in level I was defined such as the accumulation factor, the regional factor, the economic factor, the location factor, and the consortium factor. Of these, the accumulation factor(37.4%), the location factor(34.2%), and the economic factor( 24.5%) were analyzed by major factors. In level II, three assessment items of each factor were selected so that total fifteen items were formed. To sum up, the site selection of offshore wind port should consider the density of the wind industry, cargo volume of securing the economic operation of terminals, the development degree of offshore wind related industry, and the proximity to the offshore wind farms. In other words, the construction of offshore wind port should be paid attention to considering not only the proximity to offshore wind farms but also the preference of turbine manufacturing companies.
Kim, Deok-Woo;Ryu, Hong-Duck;Baek, Unil;Kim, Sunjung;Shin, Dong Seok;Lee, Jae Gwan;Chung, Eu Gene
Journal of Environmental Science International
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v.28
no.1
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pp.37-54
/
2019
The groundwater quality through livestock excreta survey based on "Act of the management and use of livestock excreta" was investigated by selecting sampling sites within 1 km of the farmland without considering hydrogeological units. However, these sites can be affected by various pollution sources such as chemical fertilizers and livestock excretions. Additionally, the effects of pollution sources on groundwater quality in the sites cannot be clearly distinguished from naturally occurring backgrounds. In this study, a method was developed to select the sampling sites for groundwater quality through livestock excreta survey in order to understand the effects of pollution sources especially livestock excreta. First, the concentrations of nitrate within the radius of 200 m, 300 m, 500 m and 750 m, respectively, from the farms regarded as pollution sources in hydrogeological units were compared in 2016-2017. All the nitrate concentrations at 200 - 500 m from the farms exceeded a background concentration, 13.3 mg/L. Those at 750 m and the background concentrations measured by the Ministry of Environment were comparable. Therefore, the appropriate radius was suggested as 500 m for livestock excretions survey. In this study, the areas within 500 m from the farms could be considered under the influence of livestock excretions, while those beyond 500 from the pollution sources as background in hydrogeological units. The developed method was validated by applying it to the sites selected based on both administrative divisions and watersheds for livestock excretion survey. The average densities for the developed method were 0.82 and 0.39 points/km2, respectively, which were considered as appropriate levels according to those of the European Environmental Agency.
Journal of the Korean Society of Marine Environment & Safety
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v.27
no.1
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pp.47-52
/
2021
Recently, the share of wind power in energy markets has sharply increased with the active development of renewable energy internationally. In particular, large-scale wind farms are being developed far from the coast to make use of abundant wind resources and to reduce noise pollution. In addition to the electromagnetic interference (EMI) caused by offshore wind farms to coastal or air surveillance radars, it is necessary to investigate the EMI on global maritime distress and safety system (GMDSS) communications between ship and coastal stations. For this purpose, this study investigates whether the transmitted field of MF/HF band from a ship would be subject to interference or attenuation below the threshold at a coastal receiver. First, using geographic information system digital maps and 3D CAD models of wind turbines, the area of interest is electromagnetically modeled with patch models. Although high frequency analysis methods like Physical Optics are appropriate to analyze wide areas compared to its wavelength, the high frequency analysis method is first verified with an accurate low frequency analysis method by simplifying the surrounding area and turbines. As a result, the received wave power is almost the same regardless of whether the wind farms are located between ships and coastal stations. From this result, although wind turbines are large structures, the size is only a few wavelengths, so it does not interfere with the electric field of MF/HF distress communications.
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.
Trong Duc Tran;Suwicha Kasemsuwan;Manakorn Sukmak;Waraphon Phimpraphai;Tippawon Prarakamawongsa;Long Thanh Pham;Tuyet Bach Hoang;Phuong Thi Nguyen;Thang Minh Nguyen;Minh Van Truong;Tuan Pham Dao;Pawin Padungtod
Journal of Veterinary Science
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v.25
no.2
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pp.20.1-20.15
/
2024
Background: Avian influenza (AI) is a contagious disease that causes illness and death in poultry and humans. High pathogenicity AI (HPAI) H5N6 outbreaks commonly occur in Quang Ninh province bordering China. In June 2021, the first HPAI H5N8 outbreak occurred at a Quang Ninh chicken farm. Objectives: This study examined the risk factors associated with HPAI H5N6 and H5N8 outbreaks in Quang Ninh. Methods: A retrospective case-control study was conducted in Quang Ninh from Nov 2021 to Jan 2022. The cases were households with susceptible poultry with two or more clinical signs and tested positive by real-time reverse transcription polymerase chain reaction. The controls were households in the same village as the cases but did not show clinical symptoms of the disease. Logistic regression models were constructed to assess the risk factors associated with HPAI outbreaks at the household level. Results: There were 38 cases with H5N6 clade 2.3.4.4h viruses (n = 35) and H5N8 clade 2.3.4.4b viruses (n = 3). Compared to the 112 controls, raising poultry in uncovered or partially covered ponds (odds ratio [OR], 7.52; 95% confidence interval [CI], 1.44-39.27), poultry traders visiting the farm (OR, 8.66; 95% CI, 2.7-27.69), farms with 50-2,000 birds (OR, 3.00; 95% CI, 1.06-8-51), and farms with ≥ 2,000 birds (OR, 11.35; 95% CI, 3.07-41.94) were significantly associated with HPAI outbreaks. Conclusions: Combining biosecurity measures, such as restricting visitor entry and vaccination in farms with more than 50 birds, can enhance the control and prevention of HPAI in Quang Ninh and its spread across borders.
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