• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.23-29
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• 2020

The National Institute of Agricultural Sciences of the Rural Developement Administration (NAS, RDA) is conducting various studies on various crops, such as monitoring the cultivation environment and analyzing harvested seeds for high-throughput phenotyping. In this paper, we propose a deep learning-based rice seed segmentation method to analyze the seeds of various crops owned by the NAS. Using Mask-RCNN deep learning model, we perform the rice seed segmentation from manually taken images under specific environment (constant lighting, white background) for analyzing the seed characteristics. For this purpose, we perform the parameter tuning process of the Mask-RCNN model. By the proposed method, the results of the test on seed object detection showed that the accuracy was 82% for rice stem image and 97% for rice grain image, respectively. As a future study, we are planning to researches of more reliable seeds extraction from cluttered seed images by a deep learning-based approach and selection of high-throughput phenotype through precise data analysis such as length, width, and thickness from the detected seed objects.

• Journal of Korean Society of Forest Science
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• v.79 no.4
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• pp.431-434
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• 1990

The growth pattern of bud-shoot-needle of isolated 15-year-old trees, and seansonal changes in litter-falls and fine root dry weights in the unthinned 28-year-old plantation were investigated to understand the growth phenology of Pinus koraiensis. Shoot growth was continued by 7th June when buds appeared, while current needle growth was by 19th July when the bud growth started. Most of the litter-falls occurred in October but many of them were fallen in July and August due to storms, Fine roots were produced mostly in autumn(1,004 kg/ha), and were dead during winter (583 kg/ha) and spring(1,331 kg/ha).

• Journal of agriculture & life science
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• v.46 no.6
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• pp.157-163
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• 2012

Pleurotus eryngii. one of the most popular edible mushrooms, has been well known for its biological activities such as antioxidation, antitumor and immune modulation. Spent coffee ground(SCG) that is a waste product from the coffee industry has been continuously investigated for its reutilization. In this study, SCG was added to the fungal cultuvation medium and analyzed for its effect on the growth and physiological activity of P. eryngii mycelia. It was clearly demonstrated that SCG could accelarate mycelia growth. 1% SCG culture was very notable by showing 2.5-fold higher dry cell weight comapred to the control culture, which suggested SCG as an excellent activator for the growth of P. eryngii mycelia. By the addition of SCG, polyphenol content was increased by two fold but there was no change in polysaccharide content. In the analysis of DPPH scavenging activity, SCG was determined as a valuable source in order to significantly increase the antioxidative activity of the mycelium.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.274-274
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• 2015

전 세계적으로 식량과 물 안보에 대한 중요도가 높아지고 있으며 이에 따라 물발자국은 식량과 물을 연계하는 요소로서 거론되고 있다. 물발자국은 제품이 생산되는 과정동안에 사용되는 물의 양을 의미하며 $m^3/ton$으로 표현한다. 이러한 물발자국은 작물 필요수량 및 생산량을 기반으로 산정되기 때문에 기후변화와 밀접한 관계가 있다. 따라서 농업 및 수자원 계획 분야에서 물발자국의 활용성을 높이기 위해서는 기후변화에 따른 우리나라 농산물의 물발자국 변화를 살펴보는 것이 필요하다. 이에 따라 본 연구에서는 기후변화에 따른 논벼의 농업용수량 및 생산량 산정을 통하여 미래의 녹색 및 청색 물발자국을 산정하고, 시기 및 시나리오별 불확실성 및 민감도를 평가하고자 하였다. 기후변화 시나리오는 RCP 기반의 신 기후변화 시나리오를 이용하였으며, 물발자국 산정 작물은 우리나라의 주곡인 논벼를 대상으로 하였다. 물발자국은 작물의 단위생산량당 소비되는 물의 양으로 정의되며, 최근 연구에서 물발자국은 용수 공급원에 따라 녹색(green), 청색(blue), 회색(grey) 물발자국으로 구분하여 산정되고 있다. 본 연구에서는 작물의 증발산으로 소비되는 수량만을 물발자국 산정에 적용하여 증발산량 중 강우에 의해 공급되는 수량인 녹색 물발자국과 관개에 의해 인위적으로 공급되는 수량인 청색물발자국을 산정하였다. 기후변화에 따른 미래의 작물의 생산량을 산정하기 위해 작물모델로 기상, 재배관리, 작물의 유전정보, 토양수분 및 질소의 효과까지 고려하여 작물의 생육뿐만 아니라 생산량까지도 모의할 수 있는 CERES-Rice모델을 적용하였다. 미래 기후 전망을 위한 전지구모형은 종류가 다양하고 모형의 특성과 모형 입력 자료에 따라 모의 결과가 상이하게 나타남에 따라 불확실성을 내포하고 있다. 따라서 기후변화에 능동적으로 대처할 수 있는 논벼의 물발자국을 산정하기 위하여 각 시나리오 및 시기별 물발자국의 불확실성 및 민감도를 분석하였다. 본 연구의 결과는 기후변화에 따른 미래 농업수자원의 변화를 분석하는데 이용될 수 있을 뿐 만아니라 우리나라 미래 국가수자원 정책의 수립을 위한 기초자료로 활용될 것으로 기대된다.

• Korean Journal of Breeding Science
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• v.43 no.5
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• pp.442-447
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• 2011

This study was carried out to assess the potential of hypocotyl explants for multiple-propagation by intensive sweetener variety with high yielding in stevia of self-fertilization. Agronomical character of self-fertilization shown a height range 72.0~120.7 cm, branch's 4.9~56.6 in stevia. Selection of high content of Rebaudioside A (RA) from segregating population in mixing variety have a variety, 'DA1' (55.2%) from HPLC analysis. On a developing of multiple-propagation in stevia, hypocotyl explants used to select for reasonable medium under the influence of each plant growth regulators concentrations. In a Mix treatment of plant growth regulators, as Murashige and Skoog medium with 1.5 mg/L BA and 0.5 mg/L Kinetin showed the most favorable. We got the multiple-propagation of 30 shoots from one inoculated hypocotyl explants as the result of these bases. Rooting induced superbly on MS medium with 0.1 mg/L IBA with inoculated shoots. All of the rooting plants were adapted to a normal seedling. This method of multi-propagation is used effectively in Rebaudioside A productivity elevation.

• Microbiology and Biotechnology Letters
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• v.47 no.3
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• pp.354-358
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• 2019

In order to evaluate the migration of fungi into doenjang from its materials, meju and solar salt, microbial communities were analyzed using pyrosequencing. Dominant fungi of meju were Botrytis spp. (57.94%) and Dothiorella samentorum (24.08%). Unidentified fungal species (37.53%), unassigned species (32.60%) and several fungal species of small portion were identified in solar salt. In doenjang, Candida versatilis were predominantly detected (92.62%). Non-halophilic mold were dominantly identified from meju (low-salt fermented soybean), while halophilic bacteria and archaea for solar salt and salt-tolerance fungi such as C. versatilis for doenjang (high-salt fermented soybean) were frequently detected. These results implied that most predominant fungal species might not be migrated from meju and/or solar salt into doenjang.

• Journal of Mushroom
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• v.19 no.1
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• pp.66-70
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• 2021

We monitored the occurrence of fungal species on bed-logs inoculated with oak mushroom (Lentinula edodes) and the environmental conditions of temperature and humidity in the cultivation houses during monsoon. Six fungal species, viz., Cladosporium sp., C. cladosporioides, C. anthropophilum, Pleosporales sp., Trichoderma harzianum, and Acremonium sp., wereidentified from the cultivation houses located in Jangheung, Jeonnam province. This identification was confirmed by performing nucleotide sequence analysis of the internal transcribed spacer and 28S rDNA regions. Our study presents significant findings that can help in preventing fungal damage induced by inappropriate temperature and humidity in oak mushroom cultivation houses.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.54-54
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• 2023

하천유역조사는 관련 법률의 규정에 의해 물관리정책의 수립에 필요한 기초정보를 제공하는 것을 목적으로 기본현황, 이수, 치수 환경생태 등 유역관리에 필요한 주요 조사항목을 대상으로 수행되고 있다. 조사방법 중 원격탐사자료 활용한 조사는 드론 모니터링 영상 및 위성영상자료를 이용해 댐·제방과 같은 치수 시설물의 안전관리, 수질 모니터링, 하천지형조사, 하상변동조사 등에 활용되고 있다. 최근에는 일반 RGB 영상뿐만 아니라 수백개의 분광밴드를 포함한 초분광영상을 이용한 하천조사 연구가 이루어지고 있다. 초분광영상은 분광해상도가 높아 다항목 조사에 활용할 수 있다는 장점이 있지만, 많은 양의 분광정보를 포함하고 있기 때문에 초기 수집 자료의 용량이 너무 크고, 분석을 위한 전처리 과정이 까다롭다는 단점이 있다. 반면, 10개 이하 밴드의 분광정보를 수집하는 다분광영상은 2개 밴드를 이용해 정규식생지수(NDVI)를 즉각적으로 모니터링할 수 있고, 작물의 생육현황 등을 분석할 수 있어 농업 및 산림분야에서 널리 활용되고 있다. 초분광영상을 이용한 수심산정 연구는 최적 밴드비 탐색 기법(OBRA)을 활용해 측정수심과 상관관계가 높은 밴드비를 이용해 수심맵을 구축하는 방식이 활용되어왔다. 본 연구에서는 기존의 초분광영상을 활용한 수심산정기법을 다분광영상에 적용하여 분광밴드수가 축소된(경량화된) 자료를 활용한 수심산정 가능성을 확인하기 위해 동일한 현장에서 초분광과 다분광 두가지 영상을 촬영하였으며, 각각 수심맵을 구축해 하천분야에서 다분광영상의 활용도를 평가하였다. 또한, 기존의 OBRA의 한계를 개선하기 위해 가우시안 혼합 모델(GMM; Gaussian Mixture Model)을 활용해 영상을 군집화하여 수심산정 정확도를 개선하였다.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.325-335
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• 1996

Visual features are crucial for monitoring the growth state, indexing the drying performance, and grading the quality of oak mushrooms. A computer vision system with neural net information processing technique was utilized to quantize quality factors of a dried oak mushrooms distributed over the cap and gill sides. In this paper, visual feature extraction algorithm were integrated with the neural net processing to deal with various fuzzy patterns of mushroom shapes and to compensate the fault sensitiveness of the crisp criteria and heuristic rules derived from the image processing results. The proposed algorithm improved the segmentation of the skin features of each side, the identification of cap and gill surfaces, the identification of stipe states and removal of the stipe, etc. And the visual characteristics of dried oak mushrooms were analyzed and primary visual features essential to tile quality evaluation were extracted and quantized. In this study, black and white gray images were captured and used for the algorithm development.

• The Journal of Bigdata
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• v.8 no.1
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• pp.1-10
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• 2023

This paper presents the design process of an agricultural data sharing platform intended to address major challenges faced by the domestic agricultural industry. The platform was designed with a user interface that prioritizes user requirements for ease of use and offers various analysis techniques to provide growth prediction for field environment, growth, management, and control data. Additionally, the platform supports File to DB and DB to DB linkage methods to ensure seamless linkage between the platform and farmhouses. The UI design process utilized HTML/CSS-based languages, JavaScript, and React to provide a comprehensive user experience from platform login to data upload, analysis, and detailed inquiry visualization. The study is expected to contribute to the development of Korean smart farm models and provide reliable data sets to agricultural industry sites and researchers.