课题基金 / 基金详情

Space-enabled Crop disEase maNagement sErvice via Crop sprAying Drones (SCENE-CAD)

Space-enabled Crop disEase maNagement sErvice via Crop sprAying Drones (SCENE-CAD)
通过作物喷洒无人机提供太空作物病害管理服务 (SCENE-CAD)
批准号:
ST/V00137X/1
负责人:
Cunjia Liu
金额:
$51.49万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
Crops diseases are widely considered as one of the main challenges in modern intensive agriculture. They not only damage crop yields and quality, posing serious threats on food security, but also exert adverse impact on the environment due to inappropriate and ineffective treatment of using excessive pesticides. The overarching goal of this project is to develop and deliver a turnkey crop disease management service to key stakeholders in China and other relevant countries, which will support them in early detection, rapid response and targeted intervention of major crop diseases. This goal will be achieved by combining a number of crop disease monitoring and forecasting technologies developed from the previous STFC UK-China Newton Agritech projects and extending their impact through integration with crop-spraying drones, so that the benefits of early identification and forecasting of crop diseases can be consolidated by rapid, targeted, and automated pesticide spraying actions. This project is structured under six main work packages (WPs), including four product/service development work packages to develop and transfer space-enabled technologies into agriculture services/tools and two demonstration work packages to encourage the acceptance of the developed services and disseminate the technologies to other countries. To facilitate the technology development/transfer, recent advances in image analysis will be assembled and utilised to extract key information from remote sensing data (WP1). Following the cycle of a dynamic crop disease management process, the project will first develop a cloud-based online service to identify, monitor and forecast hot-spot regions of overwintering wheat rusts using crop disease models, information from satellite and drone remote sensing and environmental parameters (WP2). Such information reported by the online service can be used to inform the planning and deployment of crop spraying drones to promptly control the diseases. Second, to guarantee the quality and efficacy of the pesticide delivery, an intelligent and user-friendly planning and management software for crop spraying drones will be developed (WP4), where a parametric drone spraying model (WP3) will be established to characterise spraying deposit distribution and further software tool to assess the spraying quality on different crops/diseases. The practical benefits and long-term impact of the developed products/services will be demonstrated, with the strong support from project partners in China, through two demonstration campaigns designed in this project. The first one (WP5) focuses on the overwintering wheat rusts in Gansu Province, which is the origin of inoculum that causing yield losses in the main wheat production in the Central China. It is expected that the hot-spot areas of rusts can be effectively identified using the developed service and treated using spraying drones in autumn, thus preventing or reducing the rust epidemics in spring in other regions of China. The second campaign (WP6) is dedicated to showcase the benefits in the case of rapid response to unexpected disease outbreak. The spraying missions can be automatically generated using the developed software based on the disease severity and distribution in a variable-rate manner to ensure the spraying quality while reducing operator's workload and the use of chemical pesticides and fertilisers. It is envisaged that this project will provide an integrated Agri-tech service for crop disease management that is able to improve the food productivity, reduce both the labour and pesticide costs in practice, and contribute to the long-term sustainable growth in agriculture. Moreover, through the impact activities, the project will have a profound and long-lasting impact on the local crop protection organisations, spraying service providers, drone operators and eventually the farmers, in China and beyond.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Unmanned Aerial Systems in Precision Agriculture - Technological Progresses and Applications
精准农业中的无人机系统——技术进展与应用
DOI: 10.1007/978-981-19-2027-1_7
发表时间: 2022
期刊:
影响因子: --
作者: [Su J]
通讯作者: Su J
DOI: 10.3390/rs14030782
发表时间: 2022-02
期刊: Remote. Sens.
影响因子: --
作者: [Yucheng Wang;Jinya Su;Xiaojun Zhai;Fanlin Meng;Cunjia Liu]
通讯作者: Yucheng Wang;Jinya Su;Xiaojun Zhai;Fanlin Meng;Cunjia Liu
DOI: 10.1016/j.neucom.2022.11.020
发表时间: 2022-11-12
期刊: NEUROCOMPUTING
影响因子: 6
作者: [Su, Jinya, Zhu, Xiaoyong, Chen, Wen-Hua]
通讯作者: Chen, Wen-Hua
DOI: 10.23919/icac50006.2021.9594271
发表时间: 2021
期刊:
影响因子: --
作者: [Guo Y]
通讯作者: Guo Y
9
    Autonomous landing of a helicopter at sea: advanced control in adverse conditions (AC2)
    • 批准号:
      EP/P012868/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $12.86万
    • 财政年份:
      2017
    • 负责人:
      Cunjia Liu
    • 依托单位:
    Persistence through Reliable Perching (PEP)
    • 批准号:
      EP/R005494/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $2.57万
    • 财政年份:
      2017
    • 负责人:
      Cunjia Liu
    • 依托单位:
    海外基金