• The Plant Pathology Journal
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• v.26 no.2
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• pp.198-202
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• 2010

A study was conducted to find out the relationship of physico-chemical properties (viz. organic carbon(OC), pH, electrical conductivity, nitrogen, phosphorus and potassium content) of ginger growing soil with incidence percentage of rhizome rot and wilt disease complex of ginger. Organic carbon content and pH of the ginger soil contributed significantly (93%) in the prediction of ginger rhizome rot and wilt disease complex incidence with negative correlation. Soil having weak acidic reaction with OC percent greater than 2.25 was observed to have the lower average incidence of the disease.

• Journal of Korean Society of Rural Planning
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• v.17 no.4
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• pp.75-85
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• 2011

To revitalize rural economy and to generate job opportunities in the Korean countryside through the specialized production of high-valued/environment-friendly farm products and the active promotion of green tourism in the farmland-remodelling project sites in 4 main riverside areas, this study developed the regionally differentiated development models of future-oriented agri-business complex. Through two rounds' expert group consulting/checking, related literatures review and similar case-projects benchmarking, a tentative model system was made and corrected, and finally, 6-development types with 24 model complexes proposed.

• Journal of the East Asian Society of Dietary Life
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• v.4 no.2
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• pp.39-44
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• 1994

To prepare the basic information for the fermentation of high quality persimmon vinegar in the farm. the quality of the complex fermented persimmon vinegar(CFPV) was compared to that of naturally fermented persimmon vinegar (NFPV). The titratable acidity of the CFPV was 3% which was the half concentration of the NFPV. The content of total free sugar by HPLC was 6% in CFPV and NFPV was 5%. Organic acid compositions in persimmon vinegar were oxalic acid, malic acid, lactic acid, citric acid, succinic acid and glutaric acid in addition to acetic acid. Total content of the organic acids in NFPV was higer than in CFPV. Especially, the content of latic acid in NFPV was very higher than that of CFPV. the flavour, color and taste of persimmon fruit itself in CFPV were stronger than those in NFPV.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.108-118
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• 2018

Recently, agricultural sector apply ICT technology such as Smart Farm to pursue innovation in the changing situation that is emerging as the fourth industrial revolution. However, this innovation requires techniques for forecasting and analyzing in various data bases and spatial information provides such infrastructure data. In this study, the cultivation area of Chinese cabbage, radish, garlic, onion, and red pepper were calculated and analyzed by year. The purpose of this analysis is to cope with sudden changes in vegetable crops and changes in cultivated area caused by weather changes to supply and demand of major vegetables and price instability. As a result of this study, spatial information based on time series information of vegetable complex will be used as efficient agricultural environment observation data, as well as interpretation of various spatial ranges such as the estimation of cultivation area using remote sensing.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.287-294
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• 2021

Modern small farms are important link components in the structure of the world agro-industrial complex. It ensures the food and nutritional sustainability of the country exclusively at the local regional level. The purpose of the research is to examine the role of farming in ensuring nutritional security and food stability based on the analysis of the Food Sustainability Index (FSI). Research methods: modeling, abstraction, analogy, analysis, synthesis, formalization, logical abstraction, theoretical cognition, systematization and classification, abstract-logical, etc. Results. Having analyzed the Food Sustainability Index for 2018, it has been established that there is a lack of a clear relationship between the pace of economic development and the level of food and nutritional sustainability. In addition, this study has identified the countries with the largest number of small farms, as well as the number of farms within the region. The correlation between the size of the farm and the area of agricultural land that it cultivates has been determined. The problems faced by small farms in the process of their activity have been analyzed. The programs implemented in the field of agro-industrial complex development by international profile institutions have been systematized. Particularly, the regional structure of agricultural development programs under the guidance of IFAD is defined, as well as the areas to which they are directed. Specific measures taken by governments to stimulate the development of small farms have been outlined. Reasonable conclusions have been formed based on the study. The direction of future research is seen in the assessment of the export potential of small farms in terms of range, volume of export deliveries and geographical direction of movement of their products.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.19-26
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• 2011

복잡지형에서의 풍력단지 CFD 모델링을 통한 시뮬레이션 결과가 이 논문에 주어졌다. 이 연구를 위하여 작은 산(오름)들로 둘러싸인 제주도 성산 풍력단지가 선택되었고, 두 개의 주풍향에 대하여 ANSYS CFX로 시뮬레이션 하였다. 격자생성을 위하여 실제 지형데이터가 사용되었고, 풍력발전기와 복잡지형으로부터 발생하는 후류효과를 예측하기 위하여 SST 난류모델 및 액추에이터 디스크 모델이 적용되었다. 그 결과, 성산 풍력단지 주변에 있는 작은 산 및 풍력발전기에서 발생하는 후류의 영향은 3~7 km 계속된다고 예측되었다. 또한 그 후류는 풍속 및 난류강도에 상당한 영향을 미치고 있다고 예측되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.27-30
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• 2018

We design an expert system for tomato smart farm using decision trees and construct a control system with decision structure similar to that of farmers by using the data generated by factors that vary depending on the surrounding environment of each house. At present, Smart farm's control system does not control itself like the way farmers have done so far. Therefore, the dependency of smart farm control system is still not high. Direct intervention by farmers is indispensable for environmental control based on surrounding environment such as sensor value in smart farm. Therefore, we aimed to design a controller that incorporates decision trees into the expert system to make a system similar to the decision making of farmers. Prior to controlling the equipment in the house, it automatically selects the most direct effect among the various environmental factors, and then builds an expert system for complex control by including criteria for decision making by farmers. This study focused on deriving results using data without using heavy tools. Data is coming out of many smart farms at present. We expect this to be a standard for a methodology that allows farmers to access quickly and easily and reduce direct intervention.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2011.04a
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• pp.81-91
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• 2011

Current fuel ethanol research and development deals with process engineering trends for improving biotechnological production of ethanol. Recently, a large amount of studies regarding the utilization of lignocellulosic biomass as a good feedstock for producing fuel ethanol is being carried out worldwide. The plant biomass is mainly composed of cellulose, hemicellulose and lignin. The main challenge in the conversion of biomass into ethanol is the complex, rigid and harsh structures which require efficient process and cost effective to break down. The isolation of microorganisms is one of the means for obtaining enzymes with properties suitable for industrial applications. For these reasons, crude cultures containing cellulosic biomass degrading microorganisms were isolated from rice field soil, cow farm soil and rotten rice straw from cow farm. Carboxymethyl cellulose (CMC), xylan and Avicel (microcrystalline cellulose) degradation zone of clearance on agar platefrom rice field soil resulted approximately at 25 mm, 24 mm and 22 mm respectively. As for cow farm soil, CMC, xylan and Avicel degradation clearancezone on agar plate resulted around at 24mm, 23mm and 21 mm respectively. Rotten rice straw from cow farm also resulted for CMC, xylan and Avicel degradation zone almost at 24 mm, 23 mm and 22 mm respectively. The objective of this study is to isolatebiomass degrading microbial strains having good efficiency in cellulose hydrolysis and observed the effects of different substrates (CMC, xylan and Avicel) on the production of cellulase enzymes (endo-glucanase, exo-glucanase, cellobiase, xylanase and avicelase) for producing low cost biofuel from cellulosic materials.

• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.1-10
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• 2017

The community bridge node finder, based on the stochastic method of network analysis, can compute hubs spot, which would enable the use of network structures with limited information. However, applying this node finder to heterogeneity networks, which are efficient to analyze the main farm complex in fields and the spread of infectious disease, is difficult. These problems, The most connected point that is called hub is often a major role in the heterogeneity network. In this study, we therefore improved the community bridge node finder to enable it to be applied to heterogeneity networks. We attempted to calculate the bridge node quantitatively by using the modularity of cohesion analysis method and the community bridge node finder. Application of the improved method to the HPAI(Highly Pathogenic Avian Influenza) spread in Korea 2008 produced a quarantine coefficient that was 4 - 37% higher than the quarantine coefficient obtained with the centrality method for the first 14 days after the HPAI outbreak. We concluded that the improved method has the ability to successfully calculate the bridge node in heterogeneity networks based on network structures with scant information, such as those describing the spread of infectious disease in domestic animals. And Our method should be capable to find main farm complex in fields.