• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Korean Chemical Engineering Research
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• v.45 no.2
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• pp.133-142
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• 2007

As the environmental pollution caused by excessive uses of chemical fertilizers and pesticides is aggravated, organic farming using pasture and livestock manure is gaining an increased necessity. The application rate of the organic farming materials to the field is determined as a function of crops and soil types, weather and cultivation surroundings. When livestock manure is used for organic farming materials, the volatilization of ammonia from field-spread animal manure is a major source of atmospheric pollution and leads to a significant reduction in the fertilizer value of the manure. Therefore, an ammonia emission model should be presented to reduce the ammonia emission and to know appropriate application rate of manure. In this study, the ammonia emission rate from field-applied pig manure is predicted using an artificial neural network (ANN) method, where the Michaelis-Menten equation is employed for the ammonia emission rate model. Two model parameters (total loss of ammonia emission rate and time to reach the half of the total emission rate) of the model are predicted using a feedforward-backpropagation ANN on the basis of the ALFAM (Ammonia Loss from Field-applied Animal Manure) database in Europe. The relative importance among 15 input variables influencing ammonia loss is identified using the weight partitioning method. As a result, the ammonia emission is influenced mush by the weather and the manure state.

• Journal of Bio-Environment Control
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• v.29 no.1
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• pp.73-79
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• 2020

The objective of this study is to analyze the heat transfer loss of covering materials in a single-span plastic greenhouse under the steady-state wind environment. To achieve this objective, the following were conducted: (1) design of a small-scaled wind tunnel (SCWT) to analyze heat losses of the greenhouse and its performance; (2) determination of the overall heat transfer coefficient (OHTC) for the covering materials using a small-scaled greenhouse model. The SCWT consists of the blowing, dispersion, steady flow, reduction and testing areas. Each part of the SCWT was customized and designed to maintain air flow at steady state and to minimize the variances in the SCWT test. In this study, the OHTCs of the covering materials were calculated by separating each with the roof, side wall, front and back of the small-scaled greenhouse model. The results of this study show that the OHTC of the roof increases as wind speed increases but the zones in which the increase rate of the OHTC decreased, were distinguished by wind tunnel wing speed of 2 ms^-1. For the side wall, the increase rate of the OHTC was particularly higher in the 0-1 ms^-1 zone.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.3
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• pp.95-102
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• 2015

This study conducted the survey on the resources of traditional villages based on AHP in the subjects with the specialists in Korea and China to seek the resource evaluation standards to apply the preservation and development of traditional villages, and the differences of the importance on the resources among the specialists in both countries. We classified three levels of evaluation items to aim the deductions of the importance and priority in the resources of traditional villages. Upon the analysis results, natural resources were important in the level 1; environmental, historical, facility resources were important in the level 2; and the factors such as air, topography, traditional houses, agricultural landscape, shared community facilities, interchanges between urban and rural areas, family activities, and so on were important in the level 3. The factors that both Korean and Chinese groups evaluated as the most important ones were the same. In terms of overall importance by evaluation items, the factors such as air, water quality, noise, traditional houses, topography, shared community facilities, and so on were rated as relatively important in both Korean and Chinese groups. That is, the traditional villages have the necessity to preserve the cultural resources like their duties, however, it is required to control the natural environment with good quality preferentially. This study results can compare the importance on the resources of traditional village between Korea and China. Moreover, with calculation of the priority and scores for the preservation and management of traditional villages, they are expected to be used as the tool to apply the quantitative data in the evaluation process of traditional village resources in both countries.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.9-15
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• 2011

The first objective of this study was to investigate water pollution status of Meejae Reservoir, Kunsan, irregularly receiving river water for agricultural and recreational purposes. The second objective of the study was to compare nutrient pollution loads of three nutrient sources: sediment leaching, non-point sources and the receiving water. Water analysis results showed that eutrophication was a concern especially in summer and the calculated TSI (secchi depth), TSI (chlorophyll-a), and TSI (TP) were 53.6, 57.7 and 56.7, respectively. Although there was no significant difference in seasonal mean values of sediment T-N, sediment T-P and sediment organic content, mean differences were found for sampling points. However, T-N and T-P sediment release flux showed seasonal mean differences, while showing no mean difference for sampling points. Water T-N data proportionally correlated with sediment T-N and sediment organic content data, while no statistical correlation was found for water T-P data. Comparison of nutrient loads calculated from three sources showed that the highest T-N load was occurred from the receiving (pumped) water while T-P loads of the receiving water and sediment release flux were similar. The first solution would be considered for the receiving water to improve the water quality of Meejae Reservoir. Reduction of nutrient flux from the sediment would be then tried as the second alternative solution.

• Korean Journal of Environmental Agriculture
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• v.38 no.3
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• pp.154-158
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• 2019

BACKGROUND: 'Shiranuhi' mandarin is a major cultivar among all late ripening type of citrus, and is widely cultivated in Korea. However, many farmers have reported scion root problems in their orchard resulting in reduced flowering and fruiting. It is necessary that the physiology of scion-rooted 'Shiranuhi' mandarin trees is further understood. METHODS AND RESULTS: This experiment was conducted to understand the growth response and physiology of scion-rooted 'Shiranuhi' mandarin hybrids. In our study, 'Shiranuhi' mandarin trees were divided into two groups: trees without scion roots (control) and trees with scion roots. The experiment was conducted in Seogwipo of Jeju, with ten replicates for each group. Growth of trees with scion roots was more vigorous and the trees were taller than the controls. Tree height and trunk diameter of scion-rooted trees were significantly higher than those of control trees. Exposed length of rootstocks of scion-rooted trees was significantly lower (by about 2 cm) than that of control trees (8.6 cm). In terms of root nutrition, carbon contents of scion-rooted trees was significantly lower than that of control trees, but nitrogen and potassium concentrations in scion roots were significantly higher than those in control roots. CONCLUSION: Based on the results, we infer that growth of scion-rooted trees was very vigorous and the content of nitrogen in these roots was higher than that in the control tree roots. Thus, the carbon/nitrogen ratio of scion roots was significantly lower than that of the control roots.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.270-278
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• 2022

This study was conducted using deep learning technology to classify for 'Mihwang' peach maturity with RGB images and fruit quality attributes during fruit development and maturation periods. The 730 images of peach were used in the training data set and validation data set at a ratio of 8:2. The remains of 170 images were used to test the deep learning models. In this study, among the fruit quality attributes, firmness, Hue value, and a^* value were adapted to the index with maturity classification, such as immature, mature, and over mature fruit. This study used the CNN (Convolutional Neural Networks) models for image classification; VGG16 and InceptionV3 of GoogLeNet. The performance results show 87.1% and 83.6% with Hue left value in VGG16 and InceptionV3, respectively. In contrast, the performance results show 72.2% and 76.9% with firmness in VGG16 and InceptionV3, respectively. The loss rate shows 54.3% and 62.1% with firmness in VGG16 and InceptionV3, respectively. It considers increasing for adapting a field utilization with firmness index in peach.

• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.39-52
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• 2023

There is a clear need to enhance the attractiveness of rural areas by leveraging their core assets to respond to emerging mega-trends. This paper analyzes the progress of the direct payment program that has been implemented to preserve agricultural landscapes in rural areas, using spatial information data. The study identified the planting characteristics of landscape crops, spatial utilization characteristics of the system, and utilization characteristics of the system by the beneficiaries. According to the analysis, the spatial utilization characteristics of the system could be classified into eight types: tourism resources and nearby agricultural areas, designation across the entire rural area, agricultural areas around villages, large-scale agricultural areas, small-scale agricultural areas, scattered and dispersed areas, independent parcels of land, and ranches. Based on the characteristics and limitations of the landscape preservation direct payment system, this study provides directions for future rural specialized zones. The landscape preservation direct payment system focuses on income support for farmers and providing agricultural benefits in terms of public interest. Meanwhile, the landscape agricultural zone serves as a rural specialized zone, highlighting the need to explore the direction of integrated rural landscape management. It is important for farmers, as the key stakeholders, to preserve the agricultural landscape in rural areas. Forming community-level cooperatives and engaging in relevant activities are crucial for achieving this goal. In order to actively preserve the agricultural landscape, it is necessary to consider the resumption of financial support for village landscape preservation activities, along with the designation of landscape agricultural zones. There is a need to conduct a specific review and explore measures to accommodate the designated landscape complexes at the local government level. The higher the ratio of designated landscape complexes, the more agricultural landscape management based on public value has been carried out. The designation of such landscape complexes can be seen as a demand for voluntary utilization of agricultural landscapes in the region. Moreover, as the ratio of designated landscape complexes increases, it becomes evident that farmers at the village level actively participate in agricultural landscape preservation and contribute to providing public value or utilize it as a tourism resource. This highlights the need for managing agricultural landscapes at the village level within the appropriate context.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.