• Journal of Microbiology and Biotechnology
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• v.21 no.12
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• pp.1306-1311
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• 2011

Recombinant Rhodopseudomonas palustris, harboring the carotenoid-metabolizing gene crtI (CrtIBS), and whose color changes from greenish yellow to red in response to inorganic As(III), was cultured in transparent microplate wells illuminated with a light emitting diode (LED) array. The cells were seen to grow better under near-infrared light, when compared with cells illuminated with blue or green LEDs. The absorbance ratio of 525 to 425 nm after cultivation for 24 h, which reflects red carotenoid accumulation, increased with an increase in As(III) concentrations. The detection limit of cultures illuminated with near-infrared LED was 5 ${\mu}g$/l, which was equivalent to that of cultures in test tubes illuminated with an incandescent lamp. A near-infrared LED array, in combination with a microplate, enabled the simultaneous handling of multiple cultures, including CrtIBS and a control strain, for normalization by the illumination of those with equal photon flux densities. Thus, the introduction of a near-infrared LED array to the assay is advantageous for the monitoring of arsenic in natural water samples that may contain a number of unknown factors and, therefore, need normalization of the reporter event.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.45-52
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• 2020

In the paper, we propose a system that measures various agricultural parameters that affect crop yield and monitors location information. According to an analysis by international organizations, 60% of the world's population lives on agriculture. In addition, 11% of the world's soil is used for growing crops. For this reason, agriculture plays an important role in national development. If a problem occurs in agriculture due to weather or environmental problems, it can be a problem for national development. In order to solve these problems, it is important to modernize agriculture using modern IoT technology. It is possible to improve the agricultural environment by applying IoT technology in agriculture to build a smart environment. Through such a smart environment, it is possible to increase the yield of agricultural products, reduce water waste, and prevent overuse of fertilizers. In order to verify the proposed system, an experiment was performed in a soybean cultivation farm. Experimental results showed that using the proposed system, the moisture in the cultivated soil can be automatically maintained at 40%.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.408-417
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• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• Korean journal of applied entomology
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• v.60 no.4
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• pp.357-361
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• 2021

Monitoring about nine high risk insect pests, Aceria diospyri, Bactrocera dorsalis, Bactrocera minax, Bactrocera tsuneonis, Cydia pomonella, Lobesia botrana, Proeulia sp., Solenopsis invicta and Stephanitis takeyai, were carried out in seven regions from April to October in 2020. A total of 12,045 traps/visual scouting were investigated in 222 points of 78 local sites of seven regions, resulting the nine species, A. diospyri, B. dorsalis, B. minax, B. tsuneonis, C. pomonella, L. botrana, Proeulia sp., S. invicta, and S. takeyai, were not detected. This study has been conducted from 2018 to 2020, and we established the nationwide monitoring system and secured a bridgehead for monitoring invasive insect pests passing the border including seven universities.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.753-759
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• 2011

Protected crop production has been popular in Korea as well as in other countries. Intensive and continuous monitoring and control of the environment, which is labor- and time-consuming, is critical for stable crop productivity and profitability, otherwise damage could be happened due to unfavorable ambient and soil conditions. In the study, potential utilization of smartphone and remote access application in protected crop production environment was investigated. Tested available remote access applications provided functions of mouse click (left and right buttons), zooming in and out, and screen size and color resolution control. Wi-Fi data communication speeds were affected by signal intensity and user place. Data speeds at high (> -55 dBm), medium (-70~-56 dBm), and low (< -71 dBm) signal intensity levels were statistically different (${\alpha}=0.05$). Means of data communication speed were 6.642, 4.923, and 2.906 Mbps at hot spot, home, and office, respectively, and the differences were significant at a 0.05 level. Smart phone and remote access application were applied successfully to remote monitoring (inside temperature and humidity, and outside precipitation, temperature, and humidity) and control (window and light on/off) of green house environment. Response times for monitoring and control were less than 1 s at all places for high signal intensity (> -55 dBm), but they were increased to 1 ~ 10 s at home and office and to 10 ~ 30 s at hot spot for low signal intensity (< -71 dBm) for Wi-Fi. Results of the study would provide useful information for farmers to apply these techniques for their crop production.

• International Journal of Contents
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• v.9 no.4
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• pp.22-29
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• 2013

In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.

• Journal of Forest and Environmental Science
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• v.25 no.3
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• pp.147-155
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• 2009

Higher plants provide valuable genetic assay systems for screening and monitoring environmental pollutants. They are now recognized as excellent indicators of mutagenic effects of environmental chemicals and are applicable for the detection of environmental mutagens both indoor and outdoor. 2,4-dichlorophenoxyacetic acid (2,4-D) is a herbicide commonly used in agriculture. The residues of 2,4-D are present in air, water, soil and edible plants. It constitutes a real hazard to the public health because it's wide spread use in agriculture. Genotoxic effects of 2,4-D on plant cells and potential of higher plants as a biomonitoring system for detecting chemical mutagens are evaluated. It is recommended that higher plant systems have been accepted by regulatory authorities as an alternative biomonitoring system for the detection of possible genetic damage resulting from pollution and the use of environmental chemicals.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.2
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• pp.113-123
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• 1997

This study was initiated to build runoff plots, install soil and water quality monitoring systems and collect background data from the plots and neighboring soils as the 1st year study of a 5 year project to assess soil quality and develop the management practices for environmentally sound agriculture in mountainous soils. Eleven $3{\times}15m$ runoff plots and monitoring systems were installed at a field of National Alpine Agricultural Experiment Station to monitor soil quality and discharge of nonpoint source pollutants. Corn and potato were cultivated under different fertilizer, tillage and residue cover treatments. The soil has a single-layered cluster structure that has a relatively good hydrologic properties and can adsorb a large amount of nutrient. Concentrations of T-N, $NH_4$-N, and $NO_3$-N of surface soil sampled in the winter were relatively high. Runoff quality in the winter and thawing season in the spring was largely dependent on surface freezing, snow accumulation, temperature, surface thawing depth and so on. Runoff during the thawing season caused serious soil erosion but runoff quality during the winter was relatively good. Serious wind erosion from unprotected fields after the fall harvest were obserbed and best management practices to reduce the erosion need to be developed.