• 한국농공학회논문집
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• 제47권3호
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• pp.29-37
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• 2005

This study was carried out to file up structural design data for optimizing Pleurotus eryngii growing houses. Design data are including current farm status of Pleurotus eryngii growing houses in the aspect of structural configuration as well as environmental conditions to be controlled and maintained inside. A structural analysis was performed for the on-farm structures as well as some structures modified and suggested through field survey and analysis. The results are summarized as follows. According to the results of status analysis, Pleurotus eryngii growing houses were categorized as arch-roofed simple type and sandwich panel type. Though the size of Pleurotus eryngii cultivation facilities were considerably diverse, the basic dimensions of Pleurotus eryngii cultivation facilities showed relatively similar pattern: more or less of 20m of length, $6.6\~7.0m$ of width, $4.6\~5.0m$ of peak height, $1.2\~1.6m$ of bed width, and 4 layers of bed. In the aspect of spatial use of cultivation facilities, suggested models were shown to be mostly reasonable in the aspect of heating and cooling, micro-meteorological stability, land use efficiency per unit floor area, etc.. Especially, the standard models suggested so far were thought to be not efficient in its surface area and spatial volume per unit floor area as well as its uneffective structural design in the area around ceiling. In the results of structural analysis for the models suggested through this study by using those section frames to be found on farms, the panel type structures of both single span and double span were estimated to be over designed, whereas arch-roofed pipe houses were mostly found to be under-designed.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.121-121
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• 2022

When 7 kg·10a^-1, which is less than the nitrogen standard application amount of 9 kg·10a^-1, is applied, the protein content is lowered and the palatibility is improved. In order to examine the applicability of nitrogen fertilization of 7 kg·10a^-1 nationwide, soil samples were collected from 240 paddy fields in 8 provinces in 2021, and the organic matter content, effective phosphoric acid, and effective silicic acid were analyzed for each sample. As a result of one-way ANOVA analysis between samples collected for each province, there was no significant difference in the content of organic matter, effective phosphoric acid, and effective silicic acid except for some provinces. The contents of organic matter was higher than the appropriate level(25 ~ 30 g·kg^-1) except for Gyeongsangbuk-do, the effective phosphoric acid was higher than the appropriate level(80~120 mg·kg^-1) in all provinces, and the effective silicic acid was lower than the appropriate level(157 ~ 180 mg·kg^-1) except for Gyeonggi-do, Jeollanam-do and Gyeongsangnam-do. As a result of analyzing the recommended fertilization amount based on the nitrogen application amount of 7 kg·10a^-1, 68.3% ofthe 240 samples were able to give nitrogen fertilizer less than 7.5 kg·10a^-1, and the rest had to be given more than that to satisfy the standard fertilization amount. As a result of this study, 68.3% of rice paddies nationwide can be cultivated with a standard fertilization amount of 7 kg·10a^-1, however it was thought that continuous nutrient management would be required for other paddies.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.3-6
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• 2005

In this paper, the real scenario of water situation (e.g. water management, water availability and flooding) in an irrigated rice cultivation area in Suphanburi Province, Central-West Thailand is discussed together with the NDVI time series data. The result shown is derived by our classifier named 'Peak Detector Algorithm (PDA)'. The method discriminated 5 classes in terms of irrigation activities and cropping intensities, namely, Non-irrigated, Poorly irrigated - 1 crop/year, Irrigated - 2 crops/year, Irrigated - 3 crops/year and Others (no cultivation happens in a year or other land covers). The overall accuracy of all classified results (1999-2001) is around $77\%$ against independent ground truth data (general activities or function of an area). In the classified results, spatial and temporal inconsistency appeared significantly in the Western and Southern areas of Suphanburi. The inconsistency resulted mainly by anomaly of rainfall pattern in 1999 and their temporal irrigation activity. The algorithm however, was proved that it could detect actual change of irrigation status in a year.

• 농촌지도와개발
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• 제22권4호
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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.

• 대한원격탐사학회지
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• 제38권6_1호
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• pp.1007-1014
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• 2022

차세대중형위성(Compact Advanced Satellite 500, CAS500)은 식생, 산림, 농업 등의 분야를 포함한 다양한 목적을 위하여 사용될 수 있으며, 다양한 영역에 대한 빠른 위성영상의 취득이 가능할 것으로 기대되고 있다. 차세대중형위성을 통하여 취득된 위성영상을 농업분야에서 활용하기 위해서는 위성영상 기반 작물재배지역 추출 기법에 대한 개발이 필요하다. 특히, 최근 들어 딥러닝 분야에 대한 연구가 활발해짐에 따라서, 작물재배지역 추출을 위한 딥러닝 모델의 개발 및 훈련자료 생성에 관한 연구가 필요한 실정이다. 본 연구에서는 PlanetScope 위성영상과 팜맵을 이용하여 합천군 지역의 양파 및 마늘 재배지역을 분류하고자 하였다. 특히, 효과적인 모델의 학습을 위하여 작물재배지역의 비율에 따른 모델 성능을 분석하고자 하였다. 실험에 사용한 딥러닝 모델은 Fully Convolutional Densely Connected Convolutional Network (FC-DenseNet)을 작물재배지역 분류의 목적에 맞도록 재구성하여 활용하였다. 실험결과, 훈련자료 내 작물재배지역의 비율이 딥러닝 모델의 성능에 영향을 미치는 것을 확인하였다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.208-208
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• 2017

No-tillage practices are expected to provide several benefits such as increasing soil organic matter, reducing labor time and saving energy cost compared with conventional tillage practices. This study was conducted to investigate the effects of no-tillage dry-seeding on rice growth and soil properties in comparison with other rice cultivation methods, machine transplanting and wet-hill-seeding on puddled paddy. Rice seedling establishment was slightly higher in no-tillage dry-seeding treatment ($145seedling\;m^{-2}$) than wet-hill-seeding on puddled paddy treatment ($111seedling\;m^{-2}$), but the seedling establishment in both treatments fell within the optimum range for direct seeding rice cultivation. Plant height, number of tillers and chlorophyll content (SPAD value) of rice in no-tillage dry-seeding treatment were higher than those of the other treatments. However, no significant differences in grain yield was observed among three cultivation methods, and the yield ranged 5.8 to $5.9ton\;ha^{-1}$. The heading date from seeding under no-tillage dry-seeding treatment was on average 109 days, which was similar to that under machine transplanting treatment (112 days), but 10 days later than that under wet-hill-seeding on puddled paddy treatment (99 days). Grain quality characteristics grown in no-tillage dry-seeding were similar to those grown in the other cultivation methods. These results indicate that no-tillage dry-seeding practice is comparable to conventional tillage system in terms of seedling establishment, growth, yields and grain quality.

• 한국농공학회논문집
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• 제63권6호
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• pp.27-37
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• 2021

Conversion of rice paddy field to upland has been accelerated as the central government incentivizes more profitable upland crop cultivation. The objective of this study was to investigate the current status and conversion trend from paddy to upland for the reservoir irrigation districts. Total 605 of reservoir irrigation districts whose beneficiary area is greater than 200 ha were selected for paddy-to-upland conversion analysis using the land cover maps provided by the EGIS of the Ministry of Environment. The land cover data of 2019 was used to analyze up-to-date upland conversion status and its correlation with city proximity, while land cover change between 2007 and 2019 was used for paddy-to-upland conversion trend analysis. Overall 14.8% of the entire study reservoir irrigation area was converted to upland cultivation including greenhouse and orchard areas. Approximately the portion of paddy area was reduced by 17.8% on average, while upland area was increased by 4.9% over the 12 years from 2007 to 2019. This conversion from paddy to upland cultivation was more pronounced in the Gyoenggi and Gyeongsang regions compared to other the Jeolla and Chungcheong provinces. The increase of upland area was also more notable in proximity of the major city. This study findings may assist to identify some hot reservoir districts of the rapid conversion to upland cultivation and thus plan to transition toward upland irrigation system.

• 대한원격탐사학회지
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• 제10권1호
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• pp.43-53
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• 1994

삼림을 베어서 태우고 난 직 후의 라오스 북부 화전지역의 MOS-1 위성영상을 처리하여 유역분지 단위로 화전지역의 면적을 산출하였으며, 지형도상에서 얻어낸 하계망과의 상관관계를 분석하기 위하여 PC Arc - Info의 GIS software를 이용하였다. 그 결과 화전의 분포비율이 높은 유역분지에서는 1차수하천의 분기율도 높게 나타남을 알수 있으며, 라오스에 있어서 화전이 지표 의 침식과 토지의 황폐화를 초래하여 여러가지 환경문제를 유발시키는 원인이 된다는 것이 규명 되었다.

• 대한원격탐사학회지
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• 제36권5_1호
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• pp.823-833
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• 2020

안정적인 작물 생산을 위하여 국내 농업지역에 대한 효과적인 작황 모니터링 기법의 요구가 증대되고 있다. 본 연구에서는 작물 재배지역 추출을 위하여 딥러닝 기법을 이용한 분류 모델을 개발하고, 이를 위성영상에 적용하고자 하였다. 이를 위하여, 식생분석에 유용한 blue, green, red, red-edge, NIR 밴드를 포함하고 있는 RapidEye 위성영상을 이용하여 작물 재배지역에 대한 훈련자료를 구축하고, 이를 활용하여 국내 양파 및 마늘 작물에 대한 재배면적을 추정하고자 하였다. 대기보정된 RapidEye 위성영상을 활용하여 훈련자료를 구축하였으며, 작물지역의 분류를 위하여 대표적인 의미론적 분할을 위한 딥러닝 모델인 FC-DenseNet을 이용하여 딥러닝 모델을 생성하였다. 최종적인 작물 재배지역은 지적도와의 결합을 통하여 객체 기반의 자료로 생성하였다. 실험결과, 대기보정된 훈련자료를 이용하여 학습된 FC-DenseNet 모델은 훈련에 사용되지 않은 타 지역의 작물 재배지역을 효과적으로 검출할 수 있음을 확인하였다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.362-362
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• 2017

Dissemination of IPB3S rice variety combined with cultivation technology named IPB Prima was aimed to introduce IPB research product particularly for IPB rice variety with high-yield character that is IPB3S. The rice variety IPB3S and IPB Prima cultivation technology was expected to be one of solution to improve rice productivity and accelerate to food self-sufficiency in Indonesia. Research sctivity was consist of three main research unit i.e. (1) Dissemination of IPB3S rice variety and IPB Prima production technology; (2) The development of Information and management web-based system (IMS) for planning and monitoring IPB3S and IPB Prima application distribution; and (3) The development of High-capacity grain drying system in Fluidized-bed drying ang in-store drying system. The objective of main research i.e. to introduce IPB high-yield rice variety, to accelerate rice productivity to support self-sufficiency, to develop integrated system model through fluidized and in-store drying, and to develop web-based management-information system in result analyzing IPB3S and IPB Prima distribution and technology application. The dissemination activities was arranged in two location. The first location was in Banyuwangi, East Java with total area 10.87 ha, consist of 8.91 ha planting area for IPB3S and 1.96 ha planting area for Ciherang. The second location is in Tegal, Middle Java with total planting area in 5 ha. The experiment was arranged in different treatment of varieties and cultivation method. The experiment consist of (1) rice variety Ciherang with conventional cultivation technology (P0); (2) rice variety Ciherang with IPB Prima cultivation technology (P1); (3) rice variety IPB3S with conventional cultivation technology (P2); (4) rice variety IPB3S with IPB Prima cultivation technology (P3). Planting distance for twin rows system is $50cm{\times}25cm{\times}12.5cm$. Planting distance for single row system is $25cm{\times}25cm$. The research result elucidated that productivity result in two location has different grades in similar trend. Experiment in Tegal resulted P0 result is $6.18ton\;ha^{-1}$, P1 result is $6.30ton\;ha^{-1}$, P2 result is $6.82ton\;ha^{-1}$, P3 result is $7.31ton\;ha^{-1}$. Experiment in Banyuwangi resulted optimum production of IPB3S variety productivity number are $7.29ton\;ha^{-1}$, while Ciherang are $6.73ton\;ha^{-1}$.