• Title/Summary/Keyword: Crops Information

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Automatic Control System of Green House using Whether and Smart Sensing Information (날씨정보와 스마트 센싱 정보를 이용한 비닐하우스 자동제어 시스템)

  • Jeong, Sang-Woo;Song, Teuk-Seob;Jeon, Yong-Ha;Kwak, Nae-Joung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.603-604
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    • 2017
  • In this paper, we propose system that automatically controlls greenhouse to make best environment to grow crops. The proposed system is consist of the function to automatically open and close water-roof, control the tublar well of groundwater and remote monitor information of greenhouse.

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Automtical Control System of GreenHouse Using Sensing Information (이벤트 알림서비스를 이용한 효율적인 비닐하우스 모니터링 애플리케이션)

  • Lee, Ju-Kyung;Ahn, Hyeon-Woo;Jeong, Sang-Woo;Song, Teuk-Seob;Jeon, Yong-Ha;Kim, Hae-Young;Kwak, Nae-Joung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.539-540
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    • 2017
  • In this paper, we propose system that automatically controlls greenhouse to make best environment to grow crops. The proposed system is consist of the function to automatically open and close water-roof, control the tubular well of ground water and remotely monitor information of greenhouse.

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Bridging Comparative Genomics and DNA Marker-aided Molecular Breeding

  • Choi, Hong-Kyu;Cook, Douglas R.
    • Korean Journal of Breeding Science
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    • v.43 no.2
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    • pp.103-114
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    • 2011
  • In recent years, genomic resources and information have accumulated at an ever increasing pace, in many plant species, through whole genome sequencing, large scale analysis of transcriptomes, DNA markers and functional studies of individual genes. Well-characterized species within key plant taxa, co-called "model systems", have played a pivotal role in nucleating the accumulation of genomic information and databases, thereby providing the basis for comparative genomic studies. In addition, recent advances to "Next Generation" sequencing technologies have propelled a new wave of genomics, enabling rapid, low cost analysis of numerous genomes, and the accumulation of genetic diversity data for large numbers of accessions within individual species. The resulting wealth of genomic information provides an opportunity to discern evolutionary processes that have impacted genome structure and the function of genes, using the tools of comparative analysis. Comparative genomics provides a platform to translate information from model species to crops, and to relate knowledge of genome function among crop species. Ultimately, the resulting knowledge will accelerate the development of more efficient breeding strategies through the identification of trait-associated orthologous genes and next generation functional gene-based markers.

Design and Implementation of Produce Farming Field-Oriented Smart Pest Information Retrieval System based on Mobile for u-Farm (u-Farm을 위한 모바일 기반의 농작물 재배 현장 중심형 스마트 병해충 정보검색 시스템 설계 및 구현)

  • Kang, Ju-Hee;Jung, Se-Hoon;Nor, Sun-Sik;So, Won-Ho;Sim, Chun-Bo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.10
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    • pp.1145-1156
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    • 2015
  • There is a shortage of mobile application systems readily applicable to the field of crop cultivation in relation to diseases and insect pests directly connected to the quality of crops. Most of system have been devoted to diseases and insect pests that would offer full predictions and basic information about diseases and insect pests currently. But for lack of the instant diagnostic functions seriously and the field of crop cultivation, we design and implement a crop cultivation field-oriented smart diseases and insect pests information retrieval system based on mobile for u-Farm. The proposed system had such advantages as providing information about diseases and insect pests in the field of crop cultivation and allowing the users to check the information with their smart-phones real-time based on the Lucene, a search library useful for the specialized analysis of images, and JSON data structure. And it was designed based on object-oriented modeling to increase its expandability and reusability. It was capable of search based on such image characteristic information as colors as well as the meta-information of crops and meta-information-based texts. The system was full of great merits including the implementation of u-Farm, the real-time check, and management of crop yields and diseases and insect pests by both the farmers and cultivation field managers.

The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity (농산물 생산성 향상을 위한 딥러닝 기반 농업 의사결정시스템)

  • Park, Jinuk;Ahn, Heuihak;Lee, ByungKwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.5
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    • pp.521-530
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    • 2018
  • This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

Provision of efficient online information for agricultural biotechnology

  • Lee, Bumkyu;Kim, Jong Mi
    • Korean Journal of Agricultural Science
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    • v.47 no.2
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    • pp.239-253
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    • 2020
  • This study identified consumer perceptions of biotechnology crops, provided the types and sources of information on agricultural biotech that consumers demand, and derived effective methods of providing agricultural biotech information by analyzing problems and improving the information available online regarding agricultural biotech. The analysis of sources of information on agricultural biotech showed that there were differences between preference and reliability. Respondents preferred the Internet (47.6%) and TV (36.3%), while they relied on TV (36.3%) the most, followed by the Internet (26.6%), and academic papers and technical books (23.1%). Only 27.1% of the respondents answered that they collect information on agricultural biotech proactively. The higher frequency of information collection indicated a higher satisfaction rate with the information that was being collected. Survey results for the websites that respondents preferred and relied on to collect information were that the most preferred websites were web portals (53.4%), while reliability rates across the various types of websites were relatively even: web portals (28.4%), academic institution websites (19.1%), and websites that provide professional information (18.2%). Surveys that examined factors that were important in choosing the websites for collecting information on biotech indicated that factors such as "Providing verified data and citation" and "Providing objectivity" were the most important. Examining the preferences and factors of preference by content type showed that the demand for visual aids, such as photos, tables, graphs, and videos, was high, and there were statistically significant differences between the factors of preference by content type.

Spatial Fragmentation Analysis of Upland Fields Using Farm Manager Registration Information (농업경영체 등록정보를 활용한 밭 경작지의 공간적 파편화 특성 분석)

  • Lee, Jimin;Yoo, Seung-Hwan;Oh, Yun-Gyeong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.60 no.2
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    • pp.13-24
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    • 2018
  • As food consumption pattern changes (reduced rice consumption and increased consumption of fresh vegetables), managing upland fields became a greater priority. However, the agricultural infrastructure projects have been focused on rice farming, and the infrastructure level to support dry fields cultivation is insufficient. The purpose of this study was to spatial distribution analysis of these dry fields with farm manager registration information. Using FRAGSTATS, we analyzed landscape indices (TA/CA, NP, PD, LSI, LPI, PLADJ, COHESION, CONNECT, AI) of farmlands in which farmers in 13 regions (Si or Gun) cultivated dry-field crops. As results of this analysis, the total area of the fields in Naju-si, Hampyeong-gun and Suncheon-si were found to be wider, but the average area of a patch in Youngam-gun, Hampyeong-gun and Jangseong-gun were wider than other regions. On average, each farmer had farmlands containing of 1.7~2.4 patches and cultivated crops in fields of 0.2~0.5 ha. Farmlands of Hampyeong-gun, Youngam-gun, Naju-si showed high values in adjacency indices, however the farmlands of Suncheon and Gwangyang showed fragmented distribution with low values in adjacency indices. These results of fragmentation analysis of farmlands could be used when we establish the plan of an agricultural infrastructure project or select places for a collaborative agricultural management business promotion project.

Screening of Multiple Abiotic Stress-Induced Genes in Italian Ryegrass leaves

  • Lee, Sang-Hoon;Rahman, Md. Atikur;Kim, Kwan-Woo;Lee, Jin-Wook;Ji, Hee Chung;Choi, Gi Jun;Song, Yowook;Lee, Ki-Won
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.38 no.3
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    • pp.190-195
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    • 2018
  • Cold, salt and heat are the most critical factors that restrict full genetic potential, growth and development of crops globally. However, clarification of genes expression and regulation is a fundamental approach to understanding the adaptive response of plants under unfavorable environments. In this study, we applied an annealing control primer (ACP) based on the GeneFishing approach to identify differentially expressed genes (DEGs) in Italian ryegrass (cv. Kowinearly) leaves under cold, salt and heat stresses. Two-week-old seedlings were exposed to cold ($4^{\circ}C$), salt (NaCl 200 mM) and heat ($42^{\circ}C$) treatments for six hours. A total 8 differentially expressed genes were isolated from ryegrass leaves. These genes were sequenced then identified and validated using the National Center for Biotechnology Information (NCBI) database. We identified several promising genes encoding light harvesting chlorophyll a/b binding protein, alpha-glactosidase b, chromosome 3B, elongation factor 1-alpha, FLbaf106f03, Lolium multiflorum plastid, complete genome, translation initiation factor SUI1, and glyceraldehyde-3-phosphate dehydrogenase. These genes were potentially involved in photosynthesis, plant development, protein synthesis and abiotic stress tolerance in plants. However, this study provides new insight regarding molecular information about several genes in response to multiple abiotic stresses. Additionally, these genes may be useful for enhancement of abiotic stress tolerance in fodder crops as well a crop improvement under unfavorable environmental conditions.