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苜蓿智慧管理研究进展与应用 |
王笛1, 李达1, 徐丽君2, 张德祺3, 聂莹莹2, 杨桂霞2, 薛玮2, 吴欣珈2, 范冰4, 郝建玺4
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1.白城市畜牧科学研究院;2.中国农业科学院农业资源与农业区划研究所;3.沈阳市天骏厚德通信网络工程有限公司;4.呼伦贝尔生态产业技术研究院
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摘要: |
【目的】结合现有苜蓿智慧管理研究进展,提出基于小型无人机+超声波检测在苜蓿智慧管理上的具体应用,为精准农业和苜蓿规模化生产的远程诊断提供思路。【方法】以苜蓿为研究对象,以内蒙古呼伦贝尔市谢尔塔拉农牧场为研究区,在总结归纳当前苜蓿智慧管理研究及应用现状的基础上,进行了无人机+超声波的苜蓿田数据采集及应用。【结果】研究进展表明与卫星相比,无人机在农作物识别与长势估算中,识别精度和速度表现出明显优势,苜蓿智慧管理的前提是数据的获取与分析,从无人机获取的代表苜蓿冠层高度信息的DSM数据能够显著提升苜蓿识别精度、苜蓿形态三维建模、苜蓿相对高度估算等方面,实时获取苜蓿生长过程中的相关参数使结果更为可靠。【结论】该文总结现阶段苜蓿智慧管理研究进展,归纳现有研究成果的优势与不足,提出结合无人机采集的高分辨率图像和超声传感器,对不同状况下的苜蓿进行准确数据获取的方法。基于此方法配套相应的苜蓿管理决策支持系统,将可以为用户提供苜蓿长势、产量预测和实时灌溉、施肥等管理策略。 |
关键词: 苜蓿 无人机 智慧管理 遥感 高精度 |
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基金项目:呼伦贝尔市科技计划“基于深度学习苜蓿植株形态识别与产量监测技术研究”(GX2020002)、内蒙古自治区科技成果转化专项“呼伦贝尔智慧牧场技术转化与示范”(2021CG0038)、财政部和农业农村部:现代农业产业技术体系建设专项资金(Cars-34)资助。 |
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Research progress and application of intelligent management of alfalfa |
wangdi1, LIda1, xulijun2, zhangdeqi3, nieyingying2, yangguixia2, xuewei2, wuxinjia2, fanbing4, haojianxi4
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1.Institute of Animal Husbandry Science of BaiCheng;2.Chinese Academy of Agricultural Sciences, Institute of Agricultural Resources and Regional Planning;3.Shenyang Tianjun Houde Communication Network Engineering Co;4.Hulunbuir Eco-Industry Technology Research Institute
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Abstract: |
[Purpose] In conjunction with the advancement of research in alfalfa intelligent management, the particular application of small unmanned aerial vehicle and ultrasonic detection in alfalfa intelligent management was presented to give ideas for remote diagnosis of precision agriculture and large-scale alfalfa production. [Method] Taking alfalfa as the research object and in shertaranong pasture, Hulunbuir City, Inner Mongolia as the research area, on the basis of summarizing the current research and application status of Alfalfa intelligent management, the data acquisition and application of Unmanned aerial vehicle and ultrasonic in alfalfa field are carried out. [Result] According to research, when compared to satellite unmanned aerial vehicle in a crop, it appears that the identification and estimation accuracy and speed demonstrated obvious advantages, which is the premise of alfalfa wisdom management data acquisition and analysis, from the representative of the unmanned aerial vehicle for alfalfa canopy height information of DSM data can greatly increase clover, alfalfa form three-dimensional modeling accuracy, alfalfa relative height estimate The capture of key characteristics in real-time during alfalfa growth improves the reliability of the results. [Conclusion] This paper summarized the current state of research on alfalfa intelligent management, discussed the benefits and drawbacks of existing research findings, and proposed a method for obtaining accurate data on alfalfa under various conditions by combining high-resolution images and ultrasonic sensors collected by unmanned aerial vehicle. The accompanying alfalfa management decision support system will give users alfalfa growth, yield forecast, real-time irrigation and fertilization management techniques based on this technology. |
Key words: Alfalfa Unmanned aerial vehicle Intelligent management Remote Sensing High precision |