• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.5
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• pp.27-39
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• 2022

The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.15-26
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• 2023

This study aimed to evaluate the performance of water level classification from CCTV images in agricultural facilities such as reservoirs. Recently, the CCTV system, widely used for facility monitor or disaster detection, can automatically detect and identify people and objects from the images by developing new technologies such as a deep learning system. Accordingly, we applied the ResNet-50 deep learning system based on Convolutional Neural Network and analyzed the water level of the agricultural reservoir from CCTV images obtained from TOMS (Total Operation Management System) of the Korea Rural Community Corporation. As a result, the accuracy of water level detection was improved by excluding night and rainfall CCTV images and applying measures. For example, the error rate significantly decreased from 24.39 % to 1.43 % in the Bakseok reservoir. We believe that the utilization of CCTVs should be further improved when calculating the amount of water supply and establishing a supply plan according to the integrated water management policy.

• Korean Journal of Environmental Agriculture
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• v.41 no.1
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• pp.32-40
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• 2022

BACKGROUND: Climate-smart agriculture (CSA) has been proposed for sustainable agriculture and food security in an agricultural ecosystem disturbed by climate change. However, scientific approaches to local agricultural ecosystems to realize CSA are rare. This study attempted to evaluate the weather condition, rice production, and greenhouse gas emissions from the rice cultivation in Hwaseong-si, Gyeonggi-do to fulfill CSA of the rice cultivation. METHODS AND RESULTS: Over the past 3 years (2017~2019), Chucheong rice cultivar yield and methane emissions were analyzed from the rice field plot (37°13'15"N, 127° 02'22"E) in the Gyeonggi-do Agricultural Research and Extension Services located in Gisan-dong, Hwaseong-si, Gyeonggi-do. Methane samples were collected from three automated closed chambers installed in the plot. The weather data measured through automatic weather station located in near the plot were analyzed. CONCLUSION(S): The rice productivity was found to vary with weather environment in the agricultural ecosystem. And methane emissions are high in a favorable weather condition for rice growth. Therefore, it is necessary to minimize the trade-off between the greenhouse gas emission target for climate change mitigation and productivity improvement for CSA in a local rice cultivation.

• Research in Plant Disease
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• v.26 no.3
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• pp.121-133
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• 2020

Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.2
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• pp.59-71
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• 2023

As the frequency of drought increases due to climate change, water scarcity in agriculture would be a main issue. However, it seems difficult to solve the water scarcity by securing alternative water sources. The aim of this study is to analyze optimal water supply capacity of agricultural reservoir for emergency operation connecting reservoirs and dams. First, we simulated the water storage of agricultural reservoir playing the role emergency water supplier to other water facility such as dams and other reservoirs. In particular, the results of simulation of water storage through K-HAS model was calibrated using the optimization process based on ratio correction factors of outflow and inflow. Finally, the optimal amount of water supply securing water supply reliability in emergency interconnection operation was analyzed. The results of this study showed that Janchi reservoir could supply 12.8 thousand m³/day maintaining 90 % water supply reliability. The result of this study could suggest the standard for connecting water facilities as emergency water supply.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.39-47
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• 2021

With rising concerns about pesticide spray drifts, this study analyzed the drift patterns of two typically-used nozzles, XR nozzle and AI nozzle, concerning their working pressures and wind speeds by wind tunnel experiments. AI nozzle showed low drift potential with larger droplet sizes compared to XR nozzle. Airborne and deposition drifts of XR nozzle were two times higher than those of AI nozzle under high wind speeds (≥2 m s^-1). In all cases, higher working pressures decreased the droplet sizes, thereby increasing the airborne and deposition drifts. Higher wind speeds also resulted in more airborne drifts, while ground deposition was increased under lower wind speeds. These effects of working pressures and wind speeds on the airborne and deposition drifts were observed at leeward distances less than 4 m from the nozzles. However, the airborne and deposition drifts were barely affected by the working pressures and wind speeds at leeward distances more than 11 m. The measurements were fitted to regression models of the drift curve with acceptable R² values greater than 0.8, demonstrating that further studies will be useful to settle domestic issues of spray drifts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.681-682
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• 2018

There are many damages due to the unstable climate. Among them, agriculture will be the most affected by the climate. Agriculture has limited crops that can be grown along with climate and seasons. We will develop smart farms that integrate information technology(ICT) into agricultural technology and improve the productivity of existing agricultural technology. It uses Raspberry Pi and Arduino to control the hardware and software, and uses various sensors to recognize the environment necessary for crop cultivation and maintain optimal environment. In addition, it is possible to manipulate these Smart Farm as mobile or personal PC to implement a flexible Smart Farm.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.2
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• pp.21-33
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• 2023

While the main purpose of irrigation reservoirs is to supply agricultural water, the needs of environmental flow and flood control has been expanded. The agricultural reservoirs have been operated in the form of carry-over system until now. Therefore, the supply of agricultural water is difficult when the storage rate is not sufficiently secured after large volume of irrigation. In addition, there are regulation of the upper storage rate for some large reservoirs during the flood season, but lower storage rate is not regulated. Accordingly, this study aims to evaluate the capacity of agricultural water and environmental flow supply by setting the management lower storage rate of reservoir. The changes in the supply of agricultural and environmental flow was simulated according to the three different regulating lower storage rate scenarios. As a result, it was judged effective in terms of water supply managing the lower storage rate up to 30% when the initial storage rate of farming period is above annual average for the Naju reservoir considering existing water management practice. If the lower storage rate would have been controlled above 30%, the supply of agricultural water might be increased and non-effective discharge amount would be decreased compared to other scenarios during dry period of 2016-2018.

• Journal of Korean Society of Rural Planning
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• v.26 no.4
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• pp.81-91
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• 2020

This study was conducted to analyse climate change impact on agriculture infrastructure and propose improved measures on vulnerable areas. Recently, Climate change has resulted in damaging effects on agricultural fields through increases in drought intensity and flood risk. It is expected that this impact will increase over time. This study shows that Gyeong-gi and Chung-nam provinces are affected by drought and Gyeong-buk and Gyeong-nam provinces are affected by heavy rain. However, there are also regional variations within each province. Agricultural infrastructure affected by drought may also be affected by heavy rain. Increased damages on the infrastructure due to increased extreme weather events require preventive measures especially in vulnerable areas. In order to minimize the damage by climate change, we need to introduce a reform in the system which selects project region by analysing climate change impacts. Furthermore, impact assessment of climate change from projects such as 'water supply diversification', 'flooded farmland improvement', and 'irrigation facility reinforcement' also need to be adopted to improve the measures. The results of this study are expected to provide a foundation for establishing measures on coping with climate change in the agricultural sector.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.73-81
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• 2023

To understand salinity status of fresh water and paddy soils and the susceptibility of rice to salinity stress of Gunnae reclaimed tidelands, salinity monitoring was conducted in rainy and dry seasons. For fresh water, a high salinity was observed at the sampling location near the sluice gate and decreased with distance from the gate. This spatial pattern of fresh water salinity indicates the necessity of spatial distribution of salinity in the assessment of salinity status of fresh water. Interestingly, there was significant correlation between rainfall amount and salinity, implying that salinity of fresh water varies with rainfall and thus it may be possible to predict salinity of water using rainfall. Soil salinity also higher near the gate, reflecting the influence of high saline water. In addition, the groundwater salinity also high to threat rice growth. Though soil salinity status indicated low possibility of sodium injury, there was changes in soil salinity status during the course of rice growth, suggesting that more intensive monitoring of soil salinity may be necessary for soil salinity assessment. Our study suggests the necessity of intensive salinity monitoring to understand the spatio-temporal variations of salinity of water and soil of reclaimed tideland areas.