• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.471-478
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• 2020

This study aimed to suggest implications for the future development of agricultural R&D through a priority analysis of excellent agricultural R&D performance considering productivity, marketability, and effects on region, which are important factors of agricultural R&D evaluation. The subjects of analysis were R&D of Rural Development Administration (RDA), which was selected as national R&D excellent Performance from 2006 to 2018, and the priority was analyzed using Analytic Hierarchy Process (AHP). The results are as follows. First, the relative importance of the criteria decreased in the order of marketability(0.423) > regional impact(0.360) > productivity(0.216). Second, as a result of analyzing the relative importance of the sub-criteria, the possibility of commercialization(0.515) was high in the category of marketability. The possibility of technology expansion(0.538) was high in the category of effects on region and the quality improvement(0.464) was high in the category of productivity. Third, the excellent agricultural R&D performance that had high relative importance was the technologies associated with improving the agricultural competitiveness of horticultural crops.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.218-225
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• 2020

This study analyzed the priorities of the cross-compliance items of public-benefit direct payment using an Analytic Hierarchy Process and Fuzzy Decision Making Analysis. The valuation criteria are policy efficiency, farm acceptability, and feasibility, and the valuation targets are the basic and additional cross-compliance items. The survey was performed by targeting 50 experts from each class, and conducted for about a month starting from the beginning of July 2019. The results show that the weight of the valuation criteria is higher in the order of farm acceptability, feasibility, and policy efficiency. Compliance with PLS standards, compliance with disposal standards of waste vinyl and pesticides, soil testing, compliance with toxic substance standards, education, etc. are comparatively evaluated to be higher cross-compliance items in basic cross-compliance. Disposing of an abandoned well, jointly collecting and disposing of agricultural by-products, common area care and cleaning, maintenance of empty houses and poor facilities, growing green manure crops during the fallow period, etc. are comparatively evaluated to be higher cross-compliance items for the additional cross-compliance. The results of this study are expected to contribute to the government's policy related to the cross-compliance of public-benefit direct payment.

• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.493-502
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• 2019

Maize (Zea mays L.) is a C4-plant and one of the three major crops grown worldwide. Because of its high productivity, maize is considered as one of the most important food and feed stocks in the world. Recently, bioethanol from maize was predominantly generated in the USA and Brazil. Infection of maize by several diseases resulted in a huge disaster and prevented maize production. Downy mildew, caused by Peronosclerospora sorghi, is one of the most serious diseases of maize. Despite efforts to develop downy mildew-resistant cultivars or seed treatment with metalaxyl, downy mildew persists as a serious pathogen and is still prevalent in specific geographical locations. Analysis of soils infected with downy mildew and investigation of candidates associated with downy mildew resistance is an attractive method to overcome downy mildew damage in maize. In a previous study, we reported that maize chromosome 6 carries a possible candidate gene for downy mildew resistance. Using bioinformatics tools and RT-PCR analysis, five novel genes including bZIP, OFP transcription factor, and Ppr were identified as candidate genes associated with downy mildew resistance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7761-7772
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• 2015

This study describes the spatio-temporal distributions in phytoplankton community such as species composition, standing crops and dominant species from April to November 2008 in the Jeju Marine Ranching Area (JMRA). A total of 106 species of phytoplankton belonging to 63 genera was identified. In particular, diatoms and dinoflagellates were occupied more than 61% and 35% of total species, respectively. The annual dominant species were Skeletonema costatum-like species(ls) in April, Torodinium teredo, Cylindrotheca closterium, Scrippsiella trochoidea in June, S. costatum - ls, Thalassionema nitzschioides, Pseudo-nitzschia pungens, Ebria tripartita in September and Corethron pennatum, Dictyocha fibura, Neoceratium teres in November. Phytoplankton cell density ranged between $0.6cells{\cdot}mL^{-1}$ in June and $64.0cells{\cdot}mL^{-1}$ in April. It fluctuated with an annual mean of $11.7cells{\cdot}mL^{-1}$ between the lowest value of $0.9cells{\cdot}mL^{-1}$ in November and the highest value of $37.0cells{\cdot}mL^{-1}$ by S. costatum -ls in April. Diversity index in September was higher than diatom blooming seasons in April. According to the phytoplankton community structure, the biological oceanographic characteristics of the JMRA was characterized by nanoplankton during a year. That is, primary production is deemed to have a higher possibility of being adjusted by a reproduction by material cycle in the ecosystems than nutrients supply from the lands.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.2
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• pp.100-106
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• 2012

Objectives: Diazinon is an insecticide which acts as a contact stomach and respiratory poison, and used throughout the world to control a wide range of sucking and chewing insects and mites on a range of crops. In this study, the airborne diazinon levels were measured for farmers, pest control operaters, landscapers, and agricultural chemicals sellers, and an assessment of the health risk to the workers was presented. The exposure scenario was based on the route of inhalation and skin absorption. The "OSHA Method No. 62" was used to sample and measure the airborne diazinon levels. The skin wipe method was applied to measure the level of the diazinone exposure through the skin. For the determination of exposure scenario, the exposure factors were surveyed for the daily average inhalation rate and the exposure period and frequency and time of diazinone as well as the body weight and lifetime of the workers. The median values of exposure frequency and exposure time were selected after evaluating the validity of those. Methods: The highest level of the diazinon exposure in the air was $107.21ug/m^3$ in farmers, followed by $93.53ug/m^3$ in landscapers, at $31.40ug/m^3$ in pest control operators, and $1.04ug/m^3$ in agricultural chemical seller. The amount of skin absorption was the highest in farmers at 63.39 ug/day, followed by landscapers at 10.47 ng/day, pest control operaters at 4.26 ng/day, and agricultural chemicals sellers at 0.34 ng/day. The hazardous indices calculated using toxicological reference value were 2.79 for pest control operaters, 0.41 for landscapers, 0.07 for agricultural chemicals sellers, and 0.06 for farmers. Conclusions: While the farmers were exposed to the high levels of diazinon through the air and skin, the pest control operaters, landscapers and agricultural chemicals sellers have more the diazinon hazards than the farmer based on the risk assessment in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.13-13
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• 2011

The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande Salinity Management Program. The objectives of the Rio Grande Project Salinity Management Program are to reduce salinity concentrations, loading, and salinity impacts in the Rio Grande basin for the 270 mile river reach from San Acacia, New Mexico to Fort Quitman, Texasto increase usable water supplies for agricultural, urban, and environmental purposes. The focus of this first phase of the program is the development of baseline salinity and hydrologic information and a preliminary assessment of the economic impacts of salinity. An assessment of the economic impacts of salinity in this region was conducted by scientists at Texas A&M University's AgriLife Research Center at El Paso and New Mexico State University. Economic damages attributable to high salinity of Rio Grandewater were estimated for residential, agricultural, municipal, and industrial uses. The major impact issues addressed were: who is being affected the types of economic impacts the magnitude of economic damages overall and by user category and identification of threshold-effect levels for different types of water use. Salinity concentrations in this 270 mile reach of the river typically range from 480 ppm to 1,200 ppm, but can exceed 3,000 ppm in the lower section of this reach. Economic impacts include reductions in agricultural yields, reduced water appliance life, equipment replacement costs, and increased water supply costs. This preliminary economic assessment indicates annual damages of $10.5 million from increased water salinity. Under current water uses, municipal and industrial uses account for 75% of the total estimated impacts. However, agricultural impacts are based on current crop pattern yield reductions and, salinity leaching requirements and do not account for the impacts of reduced revenue from having to grow salinity tolerant, lower value crops. Actual damages are anticipated to be significantly higher with the inclusion of these additional agricultural impacts plus the future impacts from the growing population in the region. A more comprehensive economic analysis is planned for the second phase of this program. Results of the economic analysis are being used to determine the feasiblity of salinity control alternatives and what salinity reduction control measures will be pursued.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.7-14
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• 2021

Tomato crops are highly affected by tomato diseases, and if not prevented, a disease can cause severe losses for the agricultural economy. Therefore, there is a need for a system that quickly and accurately diagnoses various tomato diseases. In this paper, we propose a system that classifies nine diseases as well as healthy tomato plants by applying various pretrained deep learning-based CNN models trained on an ImageNet dataset. The tomato leaf image dataset obtained from PlantVillage is provided as input to ResNet, Xception, and DenseNet, which have deep learning-based CNN architectures. The proposed models were constructed by adding a top-level classifier to the basic CNN model, and they were trained by applying a 5-fold cross-validation strategy. All three of the proposed models were trained in two stages: transfer learning (which freezes the layers of the basic CNN model and then trains only the top-level classifiers), and fine-tuned learning (which sets the learning rate to a very small number and trains after unfreezing basic CNN layers). SGD, RMSprop, and Adam were applied as optimization algorithms. The experimental results show that the DenseNet CNN model to which the RMSprop algorithm was applied output the best results, with 98.63% accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.231-236
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• 2021

The Aphid, Myzus persicae, and the bean bug, Riptortus clavatus, are major insects in crops. This study examined the insecticide susceptibility and phytotoxicity of insecticides dispersed using an Unmanned Aerial Vehicle (UAV, multi-copter) against the insects. Sulfoxaflor suspension concentrate (SC, 16X) on potato fields and etofenprox, methoxyfenzide suspo-emulsion(SE, 8X) on soybean fields were dispersed after deploying water-sensitive paper within the field to measure the distribution pattern and coverage index of the falling insecticide. Both insecticides showed a controlled mortality of 76.4% against aphids and 97.5% and 94.4% against the 2nd nymphal, and 5th nymphal stage of the bugs, respectively. The droplet distribution was less than 0.5mm, and coverage analysis revealed an inside and outside coverage of 3.1 and 1.6, respectively. The surrounding area was affected by insecticide spraying using a multi-copter. This study is expected to help expand UAV control and use it safely in the future.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.35-39
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• 2022

The purpose of this study was to investigate the effect of sea salt on the growth and moisture content of sweet basil, soil moisture content, and salt stress. As a research method, sweet basil was treated with sea salt at 0, 5, 50, 100, and 200 mM concentration of sea salt was investigated to determine the growth and stress time of sweet basil. As a result of the study, it was confirmed that the leaf width increased by 11% when treated with 5 mM, 49% when treated with 50 mM, and 44% when treated with 100 mM. Leaf length was confirmed to grow by 16% at 5 mM, 59% at 50 mM, and 82% at 100 mM treatment. As a future study, based on the effect of sea salt on the leaf and length growth of sweet basil by concentration, it was considered that more research is needed on the beneficial effects of sea salt on edible, medicinal, and aromatic plants. In addition, although salt has only been studied on stress in crops, we intend to contribute to providing basic data for research on ingredients more beneficial to the environment by finding various edible, medicinal, and aromatic plants using the sun-dried salt used in this study.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.1-14
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• 2023

Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.