• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.61-67
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• 2024

In order to monitor the growth environment of new varieties of crops, it is necessary to build the agricultural production infrastructure and strengthen the agricultural resource management system using popular smart sensor tag technology. In addition, the infrastructure for improving high-quality new varieties of crops using IoT technology and the monitoring system must be strengthened. In other words, widespread smart sensor (RFID UHF Sensor Tag) technology for environmental monitoring required for improving new crop varieties is desperately needed in the smart farm environment. Therefore, in this paper, we implemented an integrated sensor that can implement smart tag functions based on heterogeneous integrated sensors. In addition, we developed a technology that can manage crops in real time through the implemented smart integrated tag and smartphone linkage. For this purpose, an integrated antenna capable of RFID and Bluetooth communication was constructed. In addition, a communication method that allows information to be collected directly from the smartphone through the Bluetooth function was used.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.5
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• pp.55-65
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• 2014

Radar remote sensing is appropriate for rice monitoring because the areas where this crop is cultivated are often cloudy and rainy. Especially, Synthetic Aperture Radar (SAR) can acquire remote sensing information with a high temporal resolution in tropical and subtropical regions due to its all-weather capability. This paper analyzes the relationships between backscattering coefficients of rice measured by RADARSAT-2 SAR and growth parameters during a rice growth period. And we applied the relationships to crop monitoring of paddy rice in North Korea. As a result, plant height and Leaf Area Index (LAI) increased until Day Of Year (DOY) 234 and then decreased, while fresh weight and dry weight increased until DOY 253. Correlation coefficients revealed that Horizontal transmit and Horizontal receive polarization (HH)-polarization backscattering coefficients were correlated highly with plant height (r=0.95), fresh weight (r=0.92), vegetation water content (r=0.91), LAI (r=0.90), and dry weight (r=0.89). Based on the observed relationships between backscattering coefficients and variables of cultivation, prediction equations were developed using the HH-polarization backscattering coefficients. Concerning the evaluation for the applicability of the LAI distribution from RADARSAT-2, the LAI statistic was evaluated in comparison with LAI distribution from RapidEye image. And LAI distributions in Pyongyang were presented to show spatial variability for unaccessible areas.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.210-219
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• 2023

The decline in the rural populace and an aging workforce have led to fatalities due to worsening environments and hazards within vinyl greenhouses. Therefore, it is necessary to automate crop cultivation and disease detection system in greenhouses to prevent labor loss. In this paper, an object detection-based model is used to detect diseased crop in greenhouses. In addition, the system proposed configures the environment of the artificial intelligence model in the cloud to ensure stability. The system captures images taken inside the vinyl greenhouse and stores them in a database, and then downloads the images to the cloud to perform inference based on Yolo-v4 for detection, generating JSON files for the results. Analyze this file and send it to the database for storage. From the experimental results, it was confirmed that disease detection through object detection showed high performance in real environments like vinyl greenhouses. It was also verified that efficient monitoring is possible through the database

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1400-1402
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• 2003

The objective of this paper is to determine the suitable spectral bands for monitoring growth status change during a long period. The long-term ground-level reflectance spectra as well as LAI and biomass were obtained in xiaotangshan area, Beijing, 2001. The narrow-band NDVI type spectral indices by all possible two bands were calculated their correlation coefficients R$^2$ with biomass and LAI. The best NDVIs must have higher R$^2$ with both biomass and LAI. The reasonable band centers and band widths were determined by a systematically increasing bandwidth centered over a wavelength. In addition, the first 19 bands of MODIS were simulated and investigated. Each developed spectral indices was then validated by the biomass and LAI time series using the generalized vector angle. It turned out that six new NDVI type indices within 750-1400nm were developed. NDVI(811_10,957_10) and NDVI(962_10,802_10) performed best. No satisfactory conventional NDVI formed by red and NIR bands were found effective. MODIS_NDVI(band19, band17) and MODIS_NDVI(band19, band2) were much better than MODIS_NDVI(band2,band1) for growth monitoring.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.25-32
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• 2013

Purpose: The objective of this study is to develop a data middleware for u-IT convergence in agricultural environment monitoring, which can support non-standard data interfaces and solve the compatibility problems of heterogenous sensor networks. Methods: Six factors with three different interfaces were chosen as target data among the environmental monitoring factors for crop cultivation. PostgresSQL and PostGIS were used for database and the data middleware was implemented by Python programming language. Based on hierarchical model design and key-value type table design, the data middleware was developed. For evaluation, 2,000 records of each data access interface were prepared. Results: Their execution times of File I/O interface, SQL interface and HTTP interface were 0.00951 s/record, 0.01967 s/record and 0.0401 s/record respectively. And there was no data loss. Conclusions: The data middleware integrated three heterogenous sensor networks with different data access interfaces.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.353-353
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• 2017

Rice yield of South Korea in 2015 was the highest of the last 30 years. It is important issue to establish food policy whether the historically highest yield in 2015 can be continued or just one-off event. Therefore, it is necessary to understand whether such a high yield as 2015 will be reoccurred. The aim of this study was to find out what climatic factor affect rice yield and how often these climatic factor could occur. For this study, the yield monitoring data from National Institute of Crop Science, Rural Development Administration and the meteorological data provided by Korea Meteorological Administration are used to identify the weather conditions could cause high yield, and how often these conditions occurred in the past. Our results indicated that such as high yield as 2015 could occur only when the mean sunshine hours of July and the mean sunshine hours from the end of August to early September was more than 5.1 hours and 6 hours, respectively. Mean sunshine hour of July may be related to grain number. The mean sunshine hour from the end of August to early September was presumed to relate to grain filling ratio. The relationship between monthly mean temperature and yield or yield component was not clear in this study. In this study, any cycle of high weather condition was not found. Therefore, the probability of high yield weather condition was expressed by frequency. The frequency of the sunshine hour, could make high yield, were 8/35 (23%) over the past 35 years. And the frequency of two years consecutive sunshine hour condition, which could cause high yield, was 1/35 (2.9%). The frequency of recurrence of sunshine hour making high yield within the next 5 years or 10 years after high yield weather condition were 4/35 (11.4%). After all, the high yield as much as yield of 2015 could not be one-off event. But it was not also consecutive event.

• Food Science and Biotechnology
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• v.18 no.5
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• pp.1091-1095
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• 2009

The aim of this study investigated the fluctuations of 3 characters from 3 ecotypes [early ripening (ER), middle ripening (MR), and late ripening (LR)] of 20 Korean brown rice cultivars in different storage systems [time: 12 and 24 weeks, temperature: low ($10^{\circ}C$) and room ($25^{\circ}C$)]. With increase of storage time and temperature, lipoxygenase activity, and fat acidity increased, whereas germination rate was reduced. ER cultivars exhibited the highest lipoxygenase activity of $35.49{\pm}2.46$ unit/mg protein during 24 weeks storage at $25^{\circ}C$, followed by LR ($32.73{\pm}1.33$) and MR ($32.66{\pm}1.62$) cultivars. The amounts of fat acidity also were observed by the same order (ER: $20.40{\pm}2.12$>LR: $19.68{\pm}1.86$>MR: $19.64{\pm}1.35$ mg KOH/100 g). Germination rate slightly decreased with increase of time and temperature (MR>LR>ER), but MR and LR cultivars showed the most significant changes (ER: $60.90{\pm}23.47%$, MR: $32.66{\pm}13.95%$, and LR: $32.53{\pm}5.87%$). On the basis of above results, MR cultivars were evaluated the highest quality, because high lipoxygenase activity, high fat acidity, and low germination rate have deteriorated in quality and generated off-odor. Thus, MR cultivars might be very important sources in food processing and stored dietary supplement aspects.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.735-747
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• 2020

Recent advanced UAV (Unmanned Aerial Vehicle) technology supply new opportunities for estimating crop condition using high resolution imagery. We analyzed the diurnal change of reflectance and NDVI (Normalized Difference Vegetation Index) in UAV imagery for crop monitoring in clear day condition. Multi-spectral images were obtained from a 5-band multi-spectral camera mounted on rotary wing UAV. Reflectance were derived by the direct method using down-welling irradiance measurement. Reflectance using UAV imagery on calibration tarp, concrete and crop experimental sites did not show stable by time and daily reproducible values. But the CV (Coefficient of Variation) of diurnal NDVI on crop experimental sites was less than 5%. As a result of comparing NDVI at the similar time for two day, the daily mean average ratio of error showed a difference of 0.62 to 3.97%. Therefore, it is considered that NDVI using UAV imagery can be used for time series crop monitoring.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.733-740
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• 2017

This review introduces the empirical approach of rice yield forecasting and compares it with remote sensing approach. The empirical approach, was based on the results of the rice growth and yield monitoring experiment in 17 sites, estimated rice yield by recombination of yield components. The number of spikelet per unit area was from results of experiment sites and grain filling rate was estimated from linear regression with sunshine hours. The estimation results were relatively accurate from 2010 to 2016. The smallest error was 1 kg / 10a and the largest error was 19 kg / 10a. The largest error was caused by the typhoon. The empirical approach did not fully reflect the spatial variation caused by disasters such as typhoon or pest. On the other hand, remote sensing could explain spatial variation caused by disasters. Therefore, if there are not any disaster in rice field, both approaches are valid and remote sensing will be more accurate when any local disaster occurs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.2
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• pp.54-61
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• 2017

Rice yield of South Korea in 2015 was the highest in last 30 years. The future direction of food policy in South Korea can be determined depending on whether the historically highest yield in 2015 can be continued or just one-off event. Therefore, it is necessary to understand whether such a high yield as 2015 can be reoccurred and how often it can occur. This study used the yield monitoring data from National Institute of Crop Science, Rural Development Administration and the meteorological data provided by Korea Meteorological Administration to identify the weather conditions, which could cause high yield, and how often these conditions occurred in the past. Our results showed that significantly high yield in 2015 could occur only when the mean sunshine hours of July and the mean sunshine hours from the end of August to early September are 5.1 hours and 6 hours, respectively. The probability of satisfying these weather conditions was 8/35 (23%) over the past 35 years. And the probability of successive high yield for two years was 1/35 (2.9%). The probability of recurrence of high yield within the next 5 years or 10 years after high yield was 4/35 (11.4%).