• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.270-278
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• 2000

A machine vision system using charge coupled device(CCD) camera for the weed detection in a radish farm was developed. Shape features were analyzed with the binary images obtained from color images of radish and weeds. Aspect, Elongation and PTB were selected as significant variables for discriminant models using the STEPDISC option. The selected variables were used in the DISCRIM procedure to compute a discriminant function for classifying images into one of the two classes. Using discriminant analysis, the successful recognition rate was 92% for radish and 98% for weeds. To recognize radish and weeds more effectively than the discriminant analysis, an artificial neural network(ANN) was used. The developed ANN model distinguished the radish from the weeds with 100%. The performance of ANNs was improved to prevent overfitting and to generalize well using a regularization method. The successful recognition rate in the farms was 93.3% for radish and 93.8% for weeds. As a whole, the machine vision system using CCD camera with the artificial neural network was useful to detect weeds in the radish farms.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.22-46
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• 2005

Spatial and timely information on crop and filed conditions is one of the most important basics for rational and efficient planning and management in agriculture. Remote sensing, GIS, and modeling are powerful tools for such applications. This paper presents an overview of the state of the art in remote sensing of crop and field conditions with some case studies. It is also shown that a synergistic linkage between process-based models and remote sensing signatures enables us to estimate the multiple crop/ecosystem variables at a dynamic mode. Remotely sensed information can greatly reduce the uncertainty of simulation models by compensating for insufficient availability of data or parameters. This synergistic approach allows the effective use of infrequent and multi-source remote sensing data for estimating important ecosystem variables such as biomass growth and ecosystem $CO_2$ flux. This paper also shows a geo-spatial information system that enables us to integrate, search, extract, process, transform, and calculate any part of the data based on ID#, attributes, and/or by river-basin boundary, administrative boundary, or boundaries of arbitrary shape/size all over Japan. A case study using the system demonstrates that the nitrogen load from fertilizer was closely related to nitrate concentration of groundwater. The combined use of remote sensing, GIS and modeling would have great potential for various agro-ecosystem applications.

• Agribusiness and Information Management
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• v.4 no.2
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• pp.22-31
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• 2012

Research and technology has been transforming the agriculture to agribusiness which encompasses all operations with all the connections from faming per se, to manufacture & distribution of production supplies and farm commodities. Further, with the revolutionary development of information technology in the last two decades, we cannot talk about agribusiness process alone without considering the information technology embedded in the artifact, process, and structure. Despite the emergence of precision agriculture (PA) which is supported by IT based innovations which can not only improve efficiency in farming operations but also contribute to environmental sustainability, the adoption of IT among farmers and in agriculture industry are rather low than expected. Thus, Korean government has been seeking to converge IT into food, agriculture, forestry and fisheries to improve the competency of the agribusiness, and much progress has been made. This paper investigated the status quo of the current IT convergence with Food, Agriculture, Forestry and Fisheries in Korea, and further proposed future policy directions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3275-3298
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• 2022

Cloud-based architectures for precision agriculture are domain-specific controlled and require remote access to process and analyze the collected data over third-party cloud computing platforms. Due to the dynamic changes in agricultural parameters and restrictions in terms of accessing cloud platforms, developing a locally controlled and real-time configured architecture is crucial for efficient water irrigation and farmers management in agricultural fields. Thus, we present a new implementation of an independent sensor-enabled architecture using variety of wireless-based sensors to capture soil moisture level, amount of supplied water, and compute the reference evapotranspiration (ETo). Both parameters of soil moisture content and ETo values was then used to manage the amount of irrigated water in a small-scale agriculture field for 356 days. We collected around 34,200 experimental data samples to evaluate the performance of the architecture under different agriculture parameters and conditions, which have significant influence on realizing real-time monitoring of agricultural fields. In a proof of concept, we provide empirical results that show that our architecture performs favorably against the cloud-based architecture, as evaluated on collected experimental data through different statistical performance models. Experimental results demonstrate that the architecture has potential practical application in a many of farming activities, including water irrigation management and agricultural condition control.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.14-14
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• 2022

Greenhouse gas emissions are one of the critical factors that drive change in rice cropping systems. Within this changing system, less water irrigation and chemical fertilizer are seriously considered, as well combining precision farming technologies with irrigation control. Water and phosphorus (P) fertilizer are two of the most critical inputs in rice cultivation. Due to the lack of water availability in the system, P fertilizer is not available, especially in acidic soil conditions. Moreover, the various types of abiotic stresses, such as drought, high temperature, salinity, submergence, and limited fertilizer result in significant yield loss in the system. Even in the late stage of growth, the waves caused by diseases and insects make the field more unfruitful. Therefore, agronomists and breeders need to identify the secondary phenotypes to estimate the yield loss of when stress appears. The prediction will be clearer if we have a set of markers tagging the causal variation and the associated precise phenotype indices. Although there have been various studies for abiotic stress tolerance, we still lack functional molecular markers and phenotype indices. This is due to the underlying challenges caused by environmental factors in highly unpredictable regional and yearly environmental conditions in the field system. Pupl (phosphorus uptake 1) is still known as the first QTL associated with phosphorus uptake and have been validated in different field crops. Interestingly, some pyramiding lines of Pupl and other QTLs for other stress tolerances showed preferable phenotypes in the yield. Precise physiological studies with the help of genomics are on-going and some results will be discussed.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• The Plant Pathology Journal
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• v.35 no.6
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• pp.553-563
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• 2019

Investigations related with factors influencing root and crown rot are rare and mainly related to farming practice and soil management. The main objective of this study was to examine broader range of factors influencing stem-base infestation of winter wheat in the field conditions. The effect of spatial distribution of infected plants on disease index (DIs) assessments was also investigated. Analysis of factors influencing DIs of crown rot of wheat demonstrated significant influence of the growing seasons (P < 0.001) and extreme fluctuations in winter temperatures (P < 0.001). In addition to that, localities together with their interaction with the growing season also significantly influenced DIs (P < 0.001). Aggregation of infected plants influenced variability of DI estimations, and it was pointed out that more extensive investigation should be conducted on broad range of DI in order to establish sampling method giving uniform sampling precision. Fusarium graminearum was shown to be predominant Fusarium species in Serbia (72.6%) using sequence-characterized amplified region analysis. Interestingly F. oxysporum was isolated in higher frequencies (27.4%) than it was reported in the literature. Given that there were no reports on the diversity of Fusarium species causing crown rot of wheat in Serbia, this study presents first report on this important subject. It also indicated that more attention should be focused on combined effects of abiotic and biotic factors influencing stem-base infestation of winter wheat. This knowledge will contribute to better understanding of factors influencing root and crown rot of wheat which would ensure sustainable disease management in the future.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.203-208
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• 2006

This study was conducted to improve the control performance of a current variable-rate controller for granular fertilizers. Simulation model was developed. Optimized proportional, integral and derivative gains were determined by simulation model using 2nd order PID gain learning algorithm, and these control gains were evaluated through the field tests. Important results of this study are as follows; 1. Principles of pre-existing variable-rate application of granular fertilizers were investigated. 2. Simulation model of a PID controller that could simulate the control system was developed by using Matlab/Simulink program. The program was to determine PID control coefficients through the simulation model and 2nd order PID gain learning algorithm. 3. PID control coefficients obtained from the simulation were applied to the developed model. When the step input was given, Maximum overshoot were 1.96%, rise time were 0.05 sec, settling time were 0.06 sec and steady state error were 0.21 % respectively. 4. The simulation model was verified through field tests. The errors of maximum overshoot were 10%, rise time were 0.11 sec, settling time were 0.40 sec and steady state error were 8% because of loads and noises. Rise time was decreased to one third of that of the pre-existing system. 5. If the speed of a fertilizing machine is $0.3{\sim}0.6\;m/s$ and the maximum rotation speed of a discharging roller is 64 rpm, rise time would be 0.26 sec and fertilizing machine would cover the distance of $0.07{\sim}0.15\;m$ with settling time of 0.4 sec, fertilizing machine would cover the distance of $0.12{\sim}0.24\;m$.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.361-368
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• 2003

This study was intended to investigate the temporal and spatial variabilities of dry matter, nitrogen content, chlorophyll of paddy rice and yield caused by different rates of nitrogen application. An experimental field was divided into 45 plots of 3.48 ${\times}$ 12 m in size and application rate of nitrogen varied from 0 to 235% with an increment of 25% based on the standard rate of N-P$_2$O$_{5}$-K$_2$O=12-8-8 kg/10a. The measurements were made 8 times every 9-10 days after the transplanting. About 60 days after the transplanting, there exhibited little variabilities in the dry matter caused by different rates of nitrogen application. After that. however, there showed large variabilities and the dry matter increased with the application rate. The nitrogen content of paddy also increased with the application rate but it was inconsistent. After the tillering period, the nitrogen content remained constant. In the early stage of the tillering period the nitrogen content decreased in spite of increase in the dry matter. However. after a certain period of time it increased with the dry matter. There were little variabilities of chlorophyll after the transplanting. However, the SPAD increased with application rate of nitrogen as the paddy grew. After the tillering period SPAD was not affected by the different rates. More yield was obtained at the plots where larger nitrogen content was measured.d.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2640-2644
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• 2014

With the development of technology, wireless sensor networks (WSN) are wireless networks of consisting a large number of small and low-cost sensors. Wireless sensor networks facilitate collaboration to achieve the perception of information collection, processing and transmission tasks in deployment area. They have various purposes such as military, disaster relief, medical rescue, environmental monitoring, precision farming and manufacturing industry etc. Therefore, technologies for data maintaining technologies in sensor network environment is one of essential parts of sensor networks. In this paper, we present the essential particulars about data management technology at wireless sensor network environments and propound the issues. Further, we could organize and develop a systematic approach in solving the issues.