• Title/Summary/Keyword: Cultivation Data

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A Study on DB base Auto Cultivation of Crops Using IOT (IOT를 이용한 DB기반 농작물 자동재배에 관한 연구)

  • Cho, Youngseok
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.4
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    • pp.25-31
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    • 2017
  • In this paper, we propose a study on DB-based automatic crop cultivation that obtains crop cultivation data using IOT and automatically controls the cultivation environment using it. A system for DB-based automatic crop cultivation that automatically controls the cultivation environment is composed of a management server and a local controller. The management server was implemented using the MySQL DB in the Linux server system, and the local controller was designed and manufactured using the WiFi module and ARM Coretax-3 series MCU and confirmed its operation in the laboratory. The purpose of this study is to provide the optimal cultivation data and to grasp the cultivation status in real time when the knowledge of professional cultivation is needed like the farmers of ear farm villages. Research should continue to enable the cultivation of crops to reflect the requirements of each user.

Time-series Analysis and Prediction of Future Trends of Groundwater Level in Water Curtain Cultivation Areas Using the ARIMA Model (ARIMA 모델을 이용한 수막재배지역 지하수위 시계열 분석 및 미래추세 예측)

  • Baek, Mi Kyung;Kim, Sang Min
    • Journal of The Korean Society of Agricultural Engineers
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    • v.65 no.2
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    • pp.1-11
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    • 2023
  • This study analyzed the impact of greenhouse cultivation area and groundwater level changes due to the water curtain cultivation in the greenhouse complexes. The groundwater observation data in the Miryang study area were used and classified into greenhouse and field cultivation areas to compare the groundwater impact of water curtain cultivation in the greenhouse complex. We identified the characteristics of the groundwater time series data by the terrain of the study area and selected the optimal model through time series analysis. We analyzed the time series data for each terrain's two representative groundwater observation wells. The Seasonal ARIMA model was chosen as the optimal model for riverside well, and for plain and mountain well, the ARIMA model and Seasonal ARIMA model were selected as the optimal model. A suitable prediction model is not limited to one model due to a change in a groundwater level fluctuation pattern caused by a surrounding environment change but may change over time. Therefore, it is necessary to periodically check and revise the optimal model rather than continuously applying one selected ARIMA model. Groundwater forecasting results through time series analysis can be used for sustainable groundwater resource management.

Fundamental Research for Establishing a Job-Exposure Matrix (JEM) for Farmers Related to Insecticides (I): Rice Cultivation (농약물질 중 살충제 관련 농업 종사자들의 직무 -노출 매트릭스 구축을 위한 기초 자료 조사 연구 (I) : 수도작)

  • Kim, Ki-Youn;Cho, Man-Su;Lee, Sang-Gil;Kang, Dong-Mug;Kim, Jong-Eun
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.24 no.1
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    • pp.59-64
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    • 2014
  • Objectives: The principal aim of this study is to investigate and analyze domestic usage amounts of insecticide in rice cultivation in order to provide fundamental data for establishing a job-exposure matrix(JEM) related to farmers working with agricultural insecticides. Materials and Methods: An investigation of domestic usage amounts of insecticides rice cultivation was performed through two methods. The first method utilized information on agricultural pesticides published annually by the Korea Crop Protection Association(KCPA). The second method made use of area of cultivation of rice as officially determined by Statistics Korea(SK). An estimation of domestic usage of insecticides in rice cultivation through the second method was determined by multiplying the total cultivation area of rice($m^2$) by the optimal spray volume of insecticides for rice cultivation per unit of cultivation area($kg/m^2$). Results: As a result of the analysis of public data regarding insecticides in rice cultivation, it was found that the domestic usage amount has decreased sharply from the first year of market sales(1969) to the final data year(2012). There is little difference in the annual usage trend of insecticides in rice cultivation between shipment and estimation. Also, the annual usage trends of insecticides in rice cultivation based on regional classification were nearly similar to those based on the overall aspect. Conclusions: The region which used the largest volume of insecticide in rice cultivation in Korea was the Jeolla Provinces, followed by the Gyeonsang Provinces, the Chungcheong Provinces, Seoul/Gyeonggi Province, Gangwon Province and Jeju Province. Substantially, the mean ratio of usage amounts of insecticide based on shipments and those based on estimation by cultivation area was $96{\pm}29%$, which indicates that the domestic usage amount of insecticide for rice cultivation corresponded to the optimal spray standard per unit area.

Design of Emergency Notification Smart Farm Service Model based on Data Service for Facility Cultivation Farms Management (시설 재배 농가 관리를 위한 데이터 서비스 기반의 비상 알림 스마트팜 서비스 모델 설계)

  • Bang, Chan-woo;Lee, Byong-kwon
    • Journal of Advanced Technology Convergence
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    • v.1 no.1
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    • pp.1-6
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    • 2022
  • Since 2015, the government has been making efforts to distribute Korean smart farms. However, the supply is limited to large-scale facility vegetable farms due to the limitations of technology and current cultivation research data. In addition, the efficiency and reliability compared to the introduction cost are low due to the simple application of IT technology that does not consider the crop growth and cultivation environment. Therefore, in this paper, data analysis services was performed based on public and external data. To this end, a data-based target smart farm system was designed that is suitable for the situation of farms growing in facilities. To this end, a farm risk information notification service was developed. In addition, light environment maps were provided for proper fertilization. Finally, a disease prediction model for each cultivation crop was designed using temperature and humidity information of facility farms. Through this, it was possible to implement a smart farm data service by linking and utilizing existing smart farm sensor data. In addition, economic efficiency and data reliability can be secured for data utilization.

Economic Analysis on low Input Rice Cultivation (저투입벼 재배에 관한 경영사례분석)

  • Shin, Yong-In;Park, Joo-Sub
    • Korean Journal of Agricultural Science
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    • v.23 no.2
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    • pp.285-300
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    • 1996
  • This study is aimed to provide data of low-input rice cultivation for agricultural policy, to reveal the problems of low-input cultivation through comparing the economic result of low-input cultivation with the common one, to search for solution or mitigation of the problems of low-input cultivation, and to forecast the future prospect of low-input rice cultivation. The following were the results obtained from the survey and analysis. The working hours per 10a inputted 45.4 hours which is 32% more than 34.5 hours of common cultivation. Yield per 10a was 355kg which was 101kg less than 456kg of common cultivation. But the farm received price per kg was 1,984.9 won which was 547.9 won more than 1,436.5 won of common cultivation. Gross receipts per 10a was 704,438 won which was higher than 655,044 won of common cultivation, and management cost was 230,820 won which slightly higher than 188,157 won of common cultivation. Consequently, the income of low-input rice cultivation was 473,617 won which somewhat exceed to 466,887 won of common cultivation.

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Surface Drainage Simulation Model for Irrigation Districts Composed of Paddy and Protected Cultivation (복합영농 관개지구의 배수량 모의 모형의 개발)

  • Song, Jung-Hun;Kang, Moon-Seong;Song, Inhong;Hwang, Soon-Ho;Park, Jihoon;Ahn, Ji-Hyun
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.3
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    • pp.63-73
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    • 2013
  • The objectives of this study were to develop a hydrologic simulation model to estimate surface drainage for irrigation districts consisting of paddy and protected cultivation, and to evaluate the applicability of the developed model. The model consists of three sub-models; agricultural supply, paddy block drainage, and protected cultivation runoff. The model simulates daily total drainage as the sum of paddy field drainage, irrigation canal drainage, and protected cultivation runoff at the outlets of the irrigation districts. The agricultural supply sub-model was formulated considering crop water requirement for growing seasons and agricultural water management loss. Agricultural supply was calculated for use as input data for the paddy block sub-model. The paddy block drainage sub-model simulates paddy field drainage based on water balance, and irrigation canal drainage as a fraction of agricultural supply. Protected cultivation runoff is calculated based on NRCS (Natural Resources Conservation Service) curve number method. The Idong reservoir irrigation district was selected for surface drainage monitoring and model verification. The parameters of model were calibrated using a trial and error technique, and validated with the measured data from the study site. The model can be a useful tool to estimate surface drainage for irrigated districts consisting of paddy and protected cultivation.

Performance Evaluation of Deep Learning Model according to the Ratio of Cultivation Area in Training Data (훈련자료 내 재배지역의 비율에 따른 딥러닝 모델의 성능 평가)

  • Seong, Seonkyeong;Choi, Jaewan
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1007-1014
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    • 2022
  • Compact Advanced Satellite 500 (CAS500) can be used for various purposes, including vegetation, forestry, and agriculture fields. It is expected that it will be possible to acquire satellite images of various areas quickly. In order to use satellite images acquired through CAS500 in the agricultural field, it is necessary to develop a satellite image-based extraction technique for crop-cultivated areas.In particular, as research in the field of deep learning has become active in recent years, research on developing a deep learning model for extracting crop cultivation areas and generating training data is necessary. This manuscript classified the onion and garlic cultivation areas in Hapcheon-gun using PlanetScope satellite images and farm maps. In particular, for effective model learning, the model performance was analyzed according to the proportion of crop-cultivated areas. For the deep learning model used in the experiment, Fully Convolutional Densely Connected Convolutional Network (FC-DenseNet) was reconstructed to fit the purpose of crop cultivation area classification and utilized. As a result of the experiment, the ratio of crop cultivation areas in the training data affected the performance of the deep learning model.

A Study on Onion Wholesale Price Forecasting Model (양파 출하시기 도매가격 예측모형 연구)

  • Nam, Kuk-Hyun;Choe, Young-Chan
    • Journal of Agricultural Extension & Community Development
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    • v.22 no.4
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    • pp.423-434
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    • 2015
  • This paper predicts the onion's cultivation areas, yields per unit area, and wholesale prices during ship dates by using wholesale price data from the Korea Agro-Fisheries & Food Trade Corporation, the production data from the Statistics Korea, and the weather data from the Korea Meteorological Administration with an ARDL model. By analyzing the data of wholesale price, rural household income and rural total earnings, onion cultivation areas in 2015 are estimated to be 21,035, 17,774 and 20,557(ha). In addition, onion yields per unit area of South Jeolla Province, North Gyeongsang Province, South Gyeongsang Province, Jeju Island, and the whole country in 2015 are estimated to be 5,980, 6,493, 6,543, 6,614, 6,139 (kg/10a) respectively. By using onion production's predictive value found from onion's cultivation areas and yields per unit area in 2015, the onion's wholesale prices in June are estimated to be 780 won, 1,100 won, and 820 won for each model. Predicted monthly price after the onion's ship dates is analyzed to exceed 1,000 won after August.

Fundamental Research for Establishing Job-Exposure Matrix (JEM) of Farmer Related to Insecticide of Pesticide (II) : Vegetable (농약물질 중 살충제 관련 농업 종사자들의 직무 -노출 매트릭스 구축을 위한 기초 자료 조사 연구 (II) : 채소류)

  • Kim, Ki-Youn;Cho, Man-Su;Lim, Byung-Seo;Lee, Sang-Gil;Knag, Dong-Mug;Kim, Jong-Eun
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.24 no.3
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    • pp.293-299
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    • 2014
  • Objectives: The main objective of this study is to investigate domestic usage amount of insecticide for vegetable cultivation to provide fundamental data for establishing job-exposure matrix(JEM) related to farmers treating agricultural insecticide. Materials and Methods: The survey on domestic usage amount of insecticide for vegetable cultivation was conducted by two research methods. The first method is to utilize agricultural pesticides published annually from Korea Crop Protection Association(KCPA). The second method is to apply cultivation area of vegetable announced officially from Statistics Korea(SK). An estimation of domestic usage amount of insecticide for vegetable cultivation through the second method was done by multiplying total cultivation area of vegetable($m^2$) with optimal spray amount of insecticide for vegetable cultivation per unit cultivation area of vegetable ($kg/m^2$). Results: As a result of analysis of public data related to insecticide for vegetable cultivation, it was found that its domestic usage amount has decreased gradually from the first sale year(1969) to current year(2012). There is, however, a considerable difference of annual usage trend of insecticide for vegetable cultivation between shipments and estimation. The annual usage trends of insecticide for vegetable cultivation based on regional classification were different from those based on total aspect. Conclusions: The region which used insecticide for vegetable cultivation the most in Korea was Jeolla-do, followed by Gyeonsang-do, Chungcheong-do, Seoul/Gyeonggi-do, Gangwon-do and Jeju-do. Substantially, mean ratio of usage amounts of insecticide based on shipments and those based on estimation by cultivation area was $281{\pm}115%$, which indicates that usage amounts of insecticide estimated by cultivation area are three times lower than those based on shipments.

A Novel on a Crops Management Growth System using Web and Design Development Method

  • Jung, Se-Hoon;Kim, Jong Chan;Kim, Cheeyong
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.93-98
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    • 2017
  • A new cultivation diary system based on environment sensor data and Web 2.0 with Flex is suggested, to improve the previous system using the subjective data of cultivators. The proposed system is designed by applying an object-oriented model called mini-architecture, in order to enhance the reliability of software as well as promote stability to overall system design. The environment sensor data such as temperature and humidity are used to develop the new reliable diary. Also, an active interface based on Web 2.0 and Android as the user GUI are implemented to maximize the convenience while recording the cultivation diary. The result of the performance evaluation shows that the data from sensors has 99.1% of correlation with that of analogue.