• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.25-30
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• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.617-620
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• 2017

The periodic monitoring of crop conditions and timely estimation of crop yield are of great importance for supporting agricultural decision-makings, as well as for effectively coping with food security issues. Remote sensing has been regarded as one of effective tools for crop condition monitoring and crop type classification. Since 2010, RDA (Rural Development Administration) has been developing technology for monitoring on crop condition using remote sensing and model. These special papers address recent state-of-the-art of remote sensing and geospatial technologies for providing operational agricultural information, such as, crop yield estimation methods using remote sensing data and process-oriented model, crop classification algorithm, monitoring and prediction of weather and climate based on remote sensing data,system design and architecture of crop monitoring system, history on rice yield forecasting method.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.57-65
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• 2019

The purpose of this study was to develop an environment field monitoring system to measure crop growth. The environment field monitoring system consisted of sensors, a data acquisition system, and GPS. The sensors used in the environment field monitoring system consisted of an ambient sensor, a soil sensor, and an intensity sensor. The temperature and humidity of the atmosphere were measured with the ambient sensor. The temperature, humidity, and EC of the soil were measured with the soil sensor. The data acquisition system was developed using the Arduino controller. The field monitoring data were collected before a rainy day, on a rainy day, and after the rainy day. The measured data using the environment field monitoring system were compared with the Daejeon regional meteorological office data. The correlation between the data from the environment field monitoring system and the data from the Daejeon regional meteorological office was analyzed for performance evaluation. The correlation of the temperature and humidity of the atmosphere was analyzed because the Daejeon regional meteorological office only provided data for the temperature and humidity of the atmosphere. The correlation coefficients were 0.86 and 0.90, respectively. The result showed a good correlation between the data from the environment field monitoring system and the data from the Daejeon regional meteorological office. Therefore, the developed system could be applied to monitoring the field environment of agricultural crops.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.349-356
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• 2022

Currently, the agricultural population in Korea indicates a decreasing and aging orientation. As the population of farm labor continues to decline, so farmers are feeling the pressure to be stable crop production. To solve the problem caused by the decreasing of farm labor, it is necessary to change over to "Digital agriculture". Digital agriculture is tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture, and aims to integrate the several digital technologies into crop and livestock management and other processes in agriculture fields. In addition, digital agriculture can offer the opportunity to increase crop production, save costs for farmer. Therefore, in this study, for data-based Digital Agriculture, a greenhouse environment monitoring system for crop growth monitoring based on Node-RED, which even beginners can use easily, was developed, and the implemented system was verified in a hydroponic greenhouse. Several sensors, such as temperature, humidity, atmospheric pressure, CO₂, solar radiation, were used to obtain the environmental data of the greenhouse. And the environmental data were processed and visualized using Node-RED and MariaDB installed in rule.box digital. The environment monitoring system proposed in this study was installed in a hydroponic greenhouse and obtained the environmental data for almost two weeks. As a result, it was confirmed that all environmental data were obtained without data loss from sensors. In addition, the dashboard provides the names of installed sensors, real time environmental data, and changes in the last three days for each environmental data. Therefore, it is considered that farmers will be able to easily monitor the greenhouse environment using the developed system in this study.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.641-650
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• 2014

Now global climate change is changing environmental factors, such as temperature and precipitation, which have a great effect on crop yields. Accordingly, crop yield forecast is becoming more important to global food supplies and sustainable development of rural areas. Worldwide, many countries, such as USA, China, Canada, and institutions, such as FAO, USDA, NASA, maintain the cooperative relationship to operate the crop monitoring system at both the national and global scale. This paper aims to investigate the current developments of crop monitoring systems in terms of information level, remotely-sensed data, and biophysical parameters, and to propose the direction of the advanced corp monitoring system based on remote sensing.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.53-61
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• 2022

Growing agricultural products in greenhouses controlled by creating suitable climatic conditions and root zone of crop has been an important research and application subject. Appropriate environmental conditions in greenhouse are necessary for optimum plant growth improved crop yields. This study aimed to establish web-based remote monitoring system which monitors crops growth environment and status of crop on a real-time basis by applying to greenhouses IT technology connecting greenhouse equipment such as temperature sensors, soil sensors, crop sensors and camera. The measuring items were air temperature, relative humidity, solar radiation, CO₂ concentration, EC and pH of nutrient solution, medium temperature, EC of medium, water content of medium, leaf temperature, sap flow, stem diameter, fruit diameter, etc. The developed greenhouse monitoring system was composed of the network system, the data collecting device with sensors, and cameras. Remote monitoring system was implemented in a server/client environment. Information on greenhouse environment and crops is stored in a database. Items on growth and environment is extracted from stored information, could be compared and analyzed. So, A integrated monitoring system for smart greenhouse would be use in application practice and understanding the environment and crop growth for smart greenhouse management. sap flow, stem diameter and pant-water relations

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.751-762
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• 2017

A crop information system can provide information regarding crop distribution, crop growth conditions, crop yield in various forms such as monitoring, forecasting, estimation or analysis. This paper presents the design and construction of a crop information system based on data collected in Korea, USA, and China. Therein, climate data including temperature, precipitation,solar radiation are used to evaluate the impact on crop growth, NDVI (Normalized Difference Vegetation Index) data is used in crop monitoring, and crop map data is utilized for the management of crop distribution. The system has achieved three prominent results: 1) Providing information with high frequency, 2) Automatically creating the report through the analysis of the data, 3) The users to easily approach the system and retrieve the information.

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.10a
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• pp.415-445
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• 1998

For effective prevention of the spreading and outbreak of crop insects and disease pests, an intensive Pest surveillance system was established to predict their density changes, and distribution. After their initial establishment by either immigration or overwintering, it is necessary to anticipate how they spread out geographically and predict where/when outbreaks are possible. The two major tools, boundary layer atmospheric model (Blayer) and the geographic information system(GIS), have been being developed to facilitate the prediction of pest occurrence in recent days. We are also developing the PeMos (Pest Monitoring System) that is able to manage the pest surveillance data collected from 152 pest monitoring stations in Korea. These three system related to the pest surveillance should be integrated into an internet based comprehensive database management system to facilitate information resources systematically organized and closely linked. Considering various data types and large data size in each system, a new special information management system is suggested. The integrated system should express complex types of information, such as text, multimedia, and other scientific data under the Internet environment. This paper discussed the major three systems, GIS, Blayer, and PeMos, relevant to the crop pest surveillance, then how they can be integrated in a comprehensive system under the Internet environment.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.491-499
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• 2015

In developed countries such as USA and Europe, agricultural monitoring system is developed and utilized in various fields in order to predict crop yield, observe weather conditions and anomaly, categorize crop fields, and calculate areas for each crop. These system is Web Map Service(WMS) which utilizes open source and commercial softwares, and various information collected from remote sensing data are provided. This study will utilize tools such as GeoServer, ArcGIS Server, which are widely used to monitor agricultural production, to publish Map Server and Web Application Server. This enables performance test study for future agricultural production monitoring system by making use of response time and data transfer test. When tested in identical condition GeoServer showed a better result in response time and data transfer for performance test.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.