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云环境下作物育种信息化模型研究
引用本文:刘忠强,王开义,赵向宇,李民赞.云环境下作物育种信息化模型研究[J].农机化研究,2017(3).
作者姓名:刘忠强  王开义  赵向宇  李民赞
作者单位:1. 中国农业大学 现代精细农业系统集成研究教育部重点实验室,北京 100083; 国家农业信息化工程技术研究中心,北京 100097;2. 农业部 农业信息技术重点实验室,北京,100097;3. 北京市农业物联网工程技术研究中心,北京,100097;4. 中国农业大学 现代精细农业系统集成研究教育部重点实验室,北京,100083
基金项目:北京市科技计划项目(D151100004215002
摘    要:在种业体制改革和兼并重组加速推进、行业集中度大幅提升的大背景下,开展育种技术创新、加强资源交流与联合育种是广大中小型育种企业提升核心竞争力的必然选择。为此,首先介绍了国内作物育种信息管理软件的应用现状,对云环境下开展作物育种信息化建设的优势进行了深入分析;接着,以中小型育种企业育种信息化为业务基础,研究云服务模式与作物育种信息管理业务的契合点,提出了云环境下的作物育种信息化模型。模型充分考虑了作物育种信息管理平台在云服务模式下的个性化、一体化及差异性等特点,支持精量播种机、测产测水等农机设备的统一对接平台、面向用户特征的多层次服务提供策略和基于数据挖掘的作物育种决策支持等方案,对广大中小型育种企业、高校科研院所育种团队及专业测试机构等开展信息化建设,实现资源共享、协同育种与联合测试,进而推进现代种业全面均衡发展,具有借鉴意义。

关 键 词:育种信息化  育种软件  云服务  数据挖掘

Research on Information Model of Plant Breeding under Cloud Environment
Liu Zhongqiang,Wang Kaiyi,Zhao Xiangyu,Li Minzan.Research on Information Model of Plant Breeding under Cloud Environment[J].Journal of Agricultural Mechanization Research,2017(3).
Authors:Liu Zhongqiang  Wang Kaiyi  Zhao Xiangyu  Li Minzan
Abstract:Under the background of seed industry structure restructuring,merger and reorganization accelerating and in-dustry concentration increasing,to carry out breeding technology innovation, strengthen the resources exchanging and joint breeding is the inevitable choice of majority of small and medium enterprises to enhance the core competitiveness. Firstly, introduced currently application status of domestic plant breeding information management software,and discussed the ad-vantages of information technology under the cloud environment. Next,researched the meeting point between cloud service mode and plant breeding information management business based on information of small and medium breeding enterpri-ses,and proposed plant breeding information model under cloud environments. This model fully considered personaliza-tion,integration,differentiation and other features of plant breeding information management platform under cloud services mode,supporting unified docking platform of precision seeder, production and water test and other agricultural equip-ment,decision making of multi-level user-oriented features,and plant breeding decision support based on data mining, the main ideas are useful to the majority of small and medium enterprises,breeding team of research institutes and colle-ges,professional testing organizations to carry out information construction, resource sharing, cooperative breeding and joint testing,furthermore, to promote comprehensive and balanced development of modern seed industry.
Keywords:information breeding  breeding software  cloud services  data mining
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