• 농촌지도와개발
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• 제11권1호
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• pp.191-207
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• 2004

This study was focused on the development of greenhouse management and environmental control system using internet. The essence of this system were remote automatic control unit connected with greenhouse environmental control according to the growth stages of crops, The specific objectives of the study were; 1) to analyze need of greenhouse environmental remote control system, 2) to investigate the important functions related to greenhouse management program, 3) to explore the possibility of diffusing the system using internet.The study was carried out through review of related literature and need assessment from the research and extension workers in charge of greenhouse management using questionnaire survey, interview and field study. The results of the study were summarized as fallows: 1) About 89% of respondents responded positively on the need to establish automatic control system using internet. 2) The greenhouse management and environmental control system using internet was possible to control the greenhouse in remote, automatic, and simultaneous manner, and additionally by cellular phone in emergent situation. 3) The system was possible to precisely control the greenhouse environment, and it was able to connect the environmental control data with information on growth of crops. 4) By networking the farmer, extension educator of agricultural technology center and researcher, web based farm consulting was possible through the system. Based on the results of the study recommendations were suggested as follows: 1) Thorough spot inspections and field trials should be performed before the diffusion of this system. 2) The costs of the system installation and maintenance should be moderate. 3) The operation of the system should be simple and easy for tamers to adopt. 4) National support should be made to build better internet infrastructure in rural areas.

• 농촌지도와개발
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• 제19권3호
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• pp.699-727
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• 2012

Conditions of farm crop switching are affected by several important external factors such as agricultural products import opening, policy support, and climate change. Farming environment is always changing; barriers to imports are becoming lower and lower because of FTA and others, and climate change affects a boundary line of cultivation. Those situations give farmers motivation to change crops in order to cope with them. In addition, crop switching has been done in response to the local government measures about purchase of local agricultural products according to the local food and the expansion of organic agricultural products in school meal. Even though the favorable environment toward crop switching has been created, there are not many researches or outcomes regarding crop switching. Only few studies focus on the list of decision-making in crop switching, and locally suitable crop selection is not treated. In order to utilize crop switching as a farm management strategy, the proper frame should be studied and practical researches on application possibility also need. Therefore, study on crop switching is in a timely, proactive manner because farms catch the chance of expansion of school meal by changing crops. This paper applies HERO model used for venture foundation process to crop switching process. Success factors of HERO model are comprised of Habitate, Entrepreneurship, Resource, and Opportunity, and these phased application factors are applied to crop switching process. By doing so, each phase success factor of crop switching can be uncovered. Three farm organizations supplying organic agricultural products to schools are studied in Gyeonggi province. As a result, the stabilization stage cannot be achieved because of the habitate conditions and social conditions with low risk bearing of crop switching and current school meal systems are the main problems to block the diversification of risks. In order to succeed in crop switching, constructing the habitate in local districts or in systems of school meal is more effective than supporting each farm.

• Asian-Australasian Journal of Animal Sciences
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• 제28권5호
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• pp.703-715
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• 2015

One of the challenges to increase milk production in a large pasture-based herd with an automatic milking system (AMS) is to grow forages within a 1- km radius, as increases in walking distance increases milking interval and reduces yield. The main objective of this study was to explore sustainable forage option technologies that can supply high amount of grazeable forages for AMS herds using the Agricultural Production Systems Simulator (APSIM) model. Three different basic simulation scenarios (with irrigation) were carried out using forage crops (namely maize, soybean and sorghum) for the spring-summer period. Subsequent crops in the three scenarios were forage rape over-sown with ryegrass. Each individual simulation was run using actual climatic records for the period from 1900 to 2010. Simulated highest forage yields in maize, soybean and sorghum- (each followed by forage rape-ryegrass) based rotations were 28.2, 22.9, and 19.3 t dry matter/ha, respectively. The simulations suggested that the irrigation requirement could increase by up to 18%, 16%, and 17% respectively in those rotations in El-Nino years compared to neutral years. On the other hand, irrigation requirement could increase by up to 25%, 23%, and 32% in maize, soybean and sorghum based rotations in El-Nino years compared to La-Nina years. However, irrigation requirement could decrease by up to 8%, 7%, and 13% in maize, soybean and sorghum based rotations in La-Nina years compared to neutral years. The major implication of this study is that APSIM models have potentials in devising preferred forage options to maximise grazeable forage yield which may create the opportunity to grow more forage in small areas around the AMS which in turn will minimise walking distance and milking interval and thus increase milk production. Our analyses also suggest that simulation analysis may provide decision support during climatic uncertainty.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.263-269
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• 1996

In indian agricultural , the energy use pattern has played dominant role in influencing the level of mechanization . Besides that the agro-climatic factors as well as the size of holdings do affect the degree of mechanization . Nearly 30 percent of total cultivated area is owned by l76 percent of the small and tiny land holders each owning even less than a hectare. On the other hand, about 2 percent of land owners cultivate land. These variabilitieshave greatly influenced the ownership of power sources on Indian farms. Small farmers, employ human and animal energies with the use of hand tools and animal drawn equipments. Whereases, the use of tractors, power tillers, electric motors, etc. on small farms is on a marginal scale. There are few pockets and also extensive wheat growing regions where mechanical and electrical power sources are extensively used in production agriculture leading to about 185% of cropping intensity . In that region, the animal energy is employed for on the farm transport of fertilizers, fodders and fuel to support milch animals and other household activities . Inspite of high degree of mechanization, the harvesting of crops is done by human labour with few exceptions of harvesting wheat crops by combines in few pockets. In overall assessment of mechanization, the following conclusions are drawn : ⅰ) Farm operation which show a growing trend of mechanization are (a) tillge, (b) seedling (c) Irrigation (d) Plant protection application (e) Threshing and (f) Transport . ⅱ) Crop cultivation system in respect of wheat, maize and sorghum have been greatly mechanized. ⅲ) The least mechanized cropping systems are (a) vegetable production and (b) cultivation of sugarcane, cotton, rice and pulses. ⅳ) Annual production of tractor has touched the figure of 280.000 by 1995 and the total number has crossed 1.5million on Indian farms.

• 농업과학연구
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• 제35권1호
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• pp.69-83
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• 2008

The self-supply rate of Korea in 2006 was approximately 27.3 % by importing 13.99Mt for 19.79Mt of demanded amount. Among the imported crops, wheat, corn, and soybean consumed 95 % for the total imported amount, and wheat, corn, and soybean were 3.5Mt(Table use : 0.22Mt; Feed stuff : 0.13Mt), 8.7Mt(Table use : 0.19Mt; Feed stuff : 0.68Mt), and 1.2Mt (Table use : 0.03Mt; Feed stuff : 0.09Mt), respectively. On the other hand, our government has prepared the strategies for a great fear of food according to sharp price rise of the international crops by maintaining the self-supply rate of 5 % excluding 5.23Mt of rice in Korea. Also concern for recycled energy known as future energy for era of high oil price and global warming due to green house gas is rapidly growing. Therefore, our country which has relied on import of the whole oil needed in Korea and has to keep Kyoto Agent to request reduction of green house gas fully support research and practical use for agricultural products as resource of alternate energy. At first, we have to develop the mass production technology in order to secure a program of self-supply of food for bioenergy production utilizing agricultural product in Korea. But we assume that this matter is difficult to achieve under the current agriculture system that more emphasizes the environment conservation such as environmentally-friendly agriculture than production of food.

• 한국유기농업학회지
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• 제27권1호
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• pp.1-16
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• 2019

The questionnaire survey was conducted on 225 farmers in Gyeonggi-do, Jeollanam-do and Jeollabuk-do. A total of 189 (84%) farmers responded. 72% of the respondents were males, 50.3% were aged 60 or older, and 51.3% had less than 5 years of farming experience. 78.8% of the respondents are pesticide-free, and 44.4% of respondents have less than 0.5 ha of farming scale. 61.4% of the cultivated crops were vegetable crops. The order of seeds and seedlings to buy was tomato (23.3%), cucumber (12.2%) and pepper (10.6%). The cost of purchasing seeds ranged from a minimum of 100,000 won to a maximum of 5 million won. 78.3% of respondents answered that they well-knew or knew about organic seeds. 78.3% of respondents answered that they knew or knew about organic seeds. Of the positive effects of mandatory use of organic seeds, 41.3% of respondents said they would increase confidence in organic certification. However, 41% of respondents who opposed the mandatory use of organic seeds said that "The strengthening of regulations will make organic agriculture more difficult." When the use of organic seeds is mandatory, 43.4% of the respondents favor direct support for the purchase of organic seeds, which should be supported politically by the state. When organic seeds were supplied, the disease resistant seeds (53.4%) was the preferred characteristic of organic seeds. For the optimal price of organic seeds, 38.6% of respondents wanted the same price as the commercialized conventional seed. In this study, the questionnaire was conducted for three major organic farming regions, but many of the respondents were judged to have a legal position on the mandatory use of organic seeds. Therefore, the results of this study can be used as a basic data for reviewing the legislation on the organic seed production and distribution suitable for the situation of Korean organic farming.

• 한국농공학회논문집
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• 제64권1호
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• 대한원격탐사학회지
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• 제40권1호
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Journal of Information Science Theory and Practice
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• 제7권4호
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• 사물인터넷융복합논문지
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• 제8권2호
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• pp.71-78
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• 2022

최근 귀농을 희망하는 사람들이 증가하고 있으며 이들 대부분은 노지재배 보다는 상대적으로 소득이 높은 시설재배를 선호하는 경향이지만 부족한 영농경험과 경영정보 부재로 농업 실패 확률이 높은 실정이다. 본 연구는 시설재배를 원하는 귀농인의 초기 시설재배 경영의사결정 지원 인터페이스를 제안한다. 제안하는 인터페이스는 표준화 모델링 언어인 UML(Unified Modeling Language)로 설계되며, 사용자가 입력하는 재배지역, 선택작목, 재배형태 등의 정보에 따라 토지/작물 적합성, 토지/시설비용 및 경영비 등의 주요 의사결정 정보를 제공한다. 제안하는 인터페이스를 통해, 시설재배 희망 귀농인은 원하는 대상지에서의 시설재배를 위한 초기 의사결정 정보 획득을 통해 효과적이고 빠르며 체계적인 작물 시설재배 설계가 가능하다.