• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.93-93
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• 2020

본 연구는 7년, 13년근 산양삼의 생육특성과 진세노사이드(G) 함량 간의 상관관계를 구명하기 위하여 수행되었다. 6개소의 산양삼의 생육특성을 조사한 결과, 뇌두길이, 뿌리길이, 생중량, 단면적, 표면적, 부피에 있어 13년근 산양삼이 7년근 산양삼에 비하여 유의적으로 높은 것을 확인하였다. 진세노사이드11종에 대한 함량은 G-Rb1, Rb2, Rc, Rd, Re, Rf, Rg1, Rg2 함량이 13년근 산양삼이 7년근 산양삼 보다 유의적으로 높은 수치를 확인하였다. 또한 산양삼과 인삼(재배삼) 진세노사이드 함량을 비교한 결과, 13년 산양삼에서 G-Rb1, Rd, Re, Rf, Rg1이 4년, 5년근 인삼(재배삼)에 비해 유의적으로 함량이 높은 것으로 확인되었다. 산양삼 연근별 생육특성과 진세노사이드 함량 간의 상관관계를 분석한 결과, G-Rb1, Rb2, Rc, Rd, Re, Rf, Rg1, Rg2 함량은 뇌두길이, 생중량, 단면적, 표면적, 부피와 유의정인 정의 상관관계를 보였으며, G-Rb1, Re, Rf, Rg2는 줄기직경과 부의 상관관계를 확인하였다. 본 연구는 산양삼의 7년근과 13년근을 대상으로 생육특성과 진세노사이드 함량 상관관계를 구명함으로써 연근에 따른 품질규격 정립에 유용한 정보를 제공 할 것으로 판단된다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.04a
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• pp.110-110
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• 2019

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.04a
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• pp.111-111
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• 2019

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.6
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• pp.369-377
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• 2005

Precise application of topdressing nitrogen (N) fertilizer is indispensible for securing high yield and good quality of rice and minimizing N losses to the environment as well. For precise N management, growth and nitrogen nutrition status (NNS) should be diagnosed rapidly and accurately. The objective of the study was to evaluate the applicability of vegetation index (VI) calculated from hyperspectral canopy reflectance measurement and SPAD reading to nondestructive in situ diagnosis of growth and NNS of rice. Canopy reflectance, SPAD read­ing, growth parameters, and NNS characteristics were measured from various N treatments to evaluate the relationships among them for two cropping seasons from 2001 to 2002. The correlation coefficient of VIs with variables of growth and NNS increased positively as rice canopy became more closed. Regardless of growth stages, VIs had significantly high correlations with LAI, shoot dry weight (DW), shoot N content and nitrogen nutrition index (NNI). Those correlation coefficients increased steadily before heading stage as rice grew up. However, tiller number and leaf N concentration showed significantly high correlations with VIs only at and after panicle initiation stage (PIS). Among the VIs, RVIgreen had significantly higher correlation with the measured parameters than the other VIs: it showed correlation coefficients greater than 0.8 with leaf and shoot N concentration and DW, and much higher coefficients greater than 0.9 with LAI, shoot N content, and NNI. At LAI of below 2.5, VIs had non-significant or low correlations with the growth and NNS indicators due to the background effects. SPAD reading had significantly high correlation with leaf N concentration and NNI at each growth stage. In addition, it had significant correlations with variables of growth and NNS at PIS and booting stage, particularly, at booting stage. Though SPAD reading had a significantly high correlation value at a given growth stage in each year, it showed very weak relationship with variables of growth and NNS when pooled across growth stages and years. In conclusion, RVIgreen was found to be the most reliable VI to estimate the growth and NNS of rice around at PIS, but SPAD reading had much limitations.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.55-62
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• 2024

In this paper, we propose a thin-film hydroponic plant cultivator using HMI display and IoT technology. Existing plant cultivators were difficult to manage due to soil-based cultivation, and it was difficult to optimize environmental conditions due to the open cultivation environment. In addition, there are problems with plant cultivation as immediate control is difficult and growth of plants is delayed. To solve this problem, a cultivation environment was established by connecting the MCU and sensors, and the environment information could be checked and quickly controlled by linking with the HMI display. Additionally, a case was applied to minimize changes in environmental information. Implementation of a thin-film hydroponic cultivation system made soil management easier, improved functionality through operation and control, and made it easy to understand environmental information through the display. The effectiveness of rapid growth was confirmed through crop cultivation experiments in existing growers and hydroponic growers. Future research directions will include optimizing growth information by transmitting and storing cultivation environment information and linking and comparing growth information using vision cameras. It is expected that this will enable efficient and stable plant cultivation.

• Advanced Industrial SCIence
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• v.1 no.2
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• pp.24-29
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• 2022

Recently, smart farm research that applies IoT technology to various farms is being actively conducted to improve agricultural cooling power and minimize cost reduction. In particular, methods for automatically and remotely controlling environmental information data around smart farms through IoT devices are being studied. This paper proposes a processing model that can maintain an optimal growth environment by monitoring environmental information data collected from smart farms in real time based on machine learning. Since the proposed model uses machine learning technology, environmental information is grouped into multiple blockchains to enable continuous data collection through rich big data securing measures. In addition, the proposed model selectively (or binding) the collected environmental information data according to priority using weights and correlation indices. Finally, the proposed model allows us to extend the cost of processing environmental information to n-layer to a minimum so that we can process environmental information in real time.

• Proceedings of the Korean Society of Crop Science Conference
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• 2018.10a
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• pp.89-89
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• 2018

• Proceedings of the Korean Society of Crop Science Conference
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• 2018.10a
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• pp.90-90
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• 2018

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.5
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• pp.1-13
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• 2017

This study was intended to provide management directions through the provision of tree spatial information as basic data for the preservation of Gyerim(legal historical site), which is located in Gyeongju city, Gyeonsangnam-do, Korea. As a result of the survey of the entire forest, there are a total of 25 species and 510 individuals growing trees. Of these species, 14 species are native and 14 are introduced species. Apart from Sophora japonica, Zelkova serrata, Celtis sinensis, most of the introduced species were adopted without historical basis after designation as a historical site. By a ratio of 36% to introduced species(including 3% of naturalized species; Ailanthus altissima), the historical heritage was significantly damaged. Gyerim, which has over 2,000 years of history, has a total 15 individuals(2.9%) large trees(over 100cm DBH). Ten of these are Salix glandulosa, and in the past, most of this area was considered a Salix glandulosa forest. Currently, however, there are many small trees(under 20cm DBH) for the next generation of growth and the Salix glandulosa forest will continue to decline. Furthermore, most small trees were afforested, so the historicity and place features as a mythological forest will quickly fade.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.285-289
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• 2012

In this paper, the farm information system was designed by ubiquitous computing. The irrigation system was set up for growing forest products. Also, the integrated sensing system with the radar sensors would be constructed for sensing the temperature, the humidity and the direction of the wind, ect. And the monitoring programs for workers in the fields were provided for the control and the monitoring the growing conditions of the forest products. Finally the database was constructed for the total monitoring and management system, so the data from sensor system was stored in the database sever for analysing growing environment.