引用本文: | 沈贝贝,侯路路,丁蕾,范蓓蕾,毛平平,徐大伟,闫瑞瑞,辛晓平,陈金强.数字牧场研究进展浅析[J].中国农业信息,2021,(5):1-11 |
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摘要: |
目的 高水平管理是草原畜牧业持续发展的关键,数字化技术能够帮助牧民勘探草原生态,为牧场管理提供重要手段。数字牧场将引领牧场快速实现智慧化、定量化、精准化,综述数字牧场现状与发展趋势,展望数字牧场发展方向,助力数字牧场稳步快速发展。方法 文章通过对数字牧场相关研究文献进行系统总结,梳理相关发现和应用的最新进展,深入分析在草原背景信息获取、草原动态监测、家畜信息监测、系统过程分析和决策支持等领域的研究进展和应用状况。结果 目前我国在草原信息获取和监测等方面技术相对比较成熟,“天—空—地”一体化信息技术实现了单一技术之间的优势互补,草原的全方位立体监测有助于实现信息的空间全覆盖,具有广阔的应用前景。在家畜监测方面,实现了家畜的自动监控和智能分析,但相关研究较少,仍处于积累阶段,具有很大发展潜力。为实现草畜生产过程定量调控,开展了一系列数字化草畜监测与牧场优化管理技术研究,先后建立了多种草畜生产过程模型,能够为管理者提供决策支持,开发具有自主知识产权的软硬件产品是大势所趋。结论 随着物联网、云计算、大数据、人工智能等技术的发展和在畜牧行业的逐步落地应用,畜牧生产逐渐向数字化、智能化、智慧化发展,但是目前仍有很多不足,今后要在不断总结中取得突破和进展,在提高生产效益的同时,还要保持草原生态功能的最佳状态,促进草原生态和畜牧业生产的协调发展,进而实现草畜一体化科学发展。 |
关键词: 草原 家畜 数字化 模型 决策 |
DOI:10.12105/j.issn.1672-0423.20210501 |
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基金项目:自然科学基金项目(41771205);国家重点研发计划项目(2017YFE0104500);现代农业产业技术体系建设专项资金(CARS-34) |
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Advances of digital pasture research |
Shen Beibei1, Hou Lulu1, Ding Lei2, Fan Beilei3, Mao Pingping4, Xu Dawei1, Yan Ruirui1, Xin Xiaoping1, Chen Jinqiang1
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1.Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences / National Hulunber Grassland Ecosystem Observation and Research Station,Beijing 100081,China;2.College of Environmental and Resource Sciences,Zhejiang University,Hangzhou,310058,China;3.Agricultural Information Institute of CAAS,Beijing 100081,China;4.Nanjing Agricultural University/National Engineering and Technology Center for Information Agriculture,Jiangsu Nanjing 210095,China
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Abstract: |
Purpose High-level management is the key to the sustainable development of grassland-based livestock,and digital technology can help herders explore grassland ecology and provide important tools for pasture management. Digital pasture will lead the rapid realization of the ranch wisdom,quantification and precision. Through an overview of the status and development trend of digital pasture,the aim is to forecast the development of digital pasture direction and to help the steady and rapid development of digital pasture.Method By systematically summarizing the digital pasture-related research literature,sorting out the latest progress of related findings and applications,and deeply analyzing the research progress and application status in the fields of grassland background information acquisition,grassland dynamic monitoring,livestock information monitoring,system process analysis and decision support.Result At present,China's grassland information acquisition and monitoring technology are relatively mature. Integrated technology of satellite,aerial remote sensing,and ground internet of things have achieved the advantages of a single technology to complement each other. Grassland all-round three-dimensional monitoring has achieved full spatial coverage of information,with broad application prospects. In livestock monitoring,automatic monitoring and intelligent analysis of livestock are realized,but the related research is less and still in the accumulation stage,whose development could be very potential. In order to achieve quantitative control of grass and livestock production process,a series of digital grass and livestock monitoring and pasture optimization management technology research have been established. A variety of grass and livestock production process models could provide decision support for managers. The development of software and hardware products with independent intellectual property rights is the trend.Conclusion With the development of Internet of Things,cloud computing,big data,artificial intelligence and other technologies and their gradual application on the ground in the livestock industry,livestock production gradually develops in the direction of digitalization,intelligence and wisdom,but there are still many shortcomings. In the future,we should make breakthroughs and progress in continuous summaries,improve production efficiency while also maintaining the best state of grassland ecological function,promote the coordinated development of grassland ecology and livestock production,and then realize the scientific development of grass-livestock integration. |
Key words: grassland livestock digital models decision-making |