课题基金 / 基金详情

UK-China Agritech Challenge - Utilizing Earth Observation and UAV Technologies to Deliver Pest and Disease Products and Services to End Users in China

UK-China Agritech Challenge - Utilizing Earth Observation and UAV Technologies to Deliver Pest and Disease Products and Services to End Users in China
中英农业科技挑战赛——利用地球观测和无人机技术为中国最终用户提供病虫害产品和服务
批准号:
BB/S020977/1
负责人:
Martin Wooster
金额:
$42.14万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
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英文摘要
(KCL) This project aims to develop time-series tools for pest and disease monitoring, forecasting and management in China, providing service products at national and local levels to enhance pest and disease control of wheat rust and locusts in particular. It will also develop advanced UAV-based tools that provide more efficient spraying of control measures (biopesticides) to provide alleviation of these problems without causing chemical pollution. In this context, the King's team will be developing ways to downscale satellite-based maps of land surface temperature to scales more akin to those of the fields within which the crops grow, in order to aid the development of mathematical models that can be used to forecast and monitor the efficacy of the bio-control measures and the spread of wheat rust. They will develop UAV-based methods to deliver maps of crop parameters from aerial imagery, which will be used to help both development of the downscaled satellite datasets and to provide an understanding of the crop structures that can be used to help in the development of the spraying technologies and planning tools that will be developed for the aerial platforms. Finally they will also develop methods to remotely sense locust surface temperatures from thermal imaging, in order to contribute to the development of better models of locust internal body temperature upon which the final mathematical models of bio-pesticide development rate depends.(Loughborough) Our proposal aims to develop a long term sustainable innovative partnership in agriculture technology between the UK and China through a comprehensive approach to deal with these two major agricultural pests/diseases. It will do so from a monitoring,forecasting and management perspective, combining cutting edge technology, modelling and biological information.The project is structured under six work packages that follow the cycle of a dynamic Agri-Tech service: observe to understand the nature of the problem and locate the pest/crop problem (WP1), orientate through development of forecast models to provide strategic risk awareness (WP2), decide providing useful information where to control pests at national and local levels (WP3), and act locally using precise application of bio pesticides via UAV deployments (WP4). The scopeof the project primarily falls into Agri-Tech Challenge 1 "Precision agriculture, agriculture digitisation and decision management tools" but also makes significant contributions to Challenge 2 "Improving the efficiency of sustainable agriculture". A key theme is to develop technologies for integrating data collected by UAVs, earth observation satellites,and bioscience applications related to disease/pest modelling. The project will develop autonomous and smart planning tools for agricultural remote sensing and plant protection, ultimately for the benefit of end users to reduce the cost and improve the effectiveness of their operations. One of the key outcomes is the development and application of novel technical systems for the monitoring and prediction of crop disease/pest outbreaks, As a novel technology, biopesticides treatment of orthoptera will be investigated and demonstrated, along with the modelling and prediction of yellow rust and orthoptera, real-time remote sensing methods will facilitate time specific and site specific treatment along with improved general farming management. Combining this with the work on biopesticides will significantly reduce the use of chemical pesticides and the risk of the development of crop's resistance to them, and will increase biodiversity due to lack of chemical pesticides. In addition to these benefits, the project will open up new business opportunities for both the UK, and Chinese industrial partners outside of China.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.compag.2020.105282
发表时间: 2020-03-01
期刊: COMPUTERS AND ELECTRONICS IN AGRICULTURE
影响因子: 8.3
作者: [Meng, Yanhua, Su, Jinya, Lan, Yubin]
通讯作者: Lan, Yubin
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
DOI: 10.1016/j.compag.2022.106807
发表时间: 2022-05
期刊: Comput. Electron. Agric.
影响因子: --
作者: [M. Coombes;Sam Newton;James Knowles;A. Garmory]
通讯作者: M. Coombes;Sam Newton;James Knowles;A. Garmory
NERC Earth Observation Data Analysis and Artificial-Intelligence Service (NEODAAS)
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    NE/Y005406/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $333.21万
  • 财政年份:
    2024
  • 负责人:
    Martin Wooster
  • 依托单位:
NERC Field Spectroscopy Facility (FSF)
  • 批准号:
    NE/Y005392/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $177.38万
  • 财政年份:
    2024
  • 负责人:
    Martin Wooster
  • 依托单位:
Development and application of Earth Observation to support reductions in methane emission from agriculture (EOforCH4)
  • 批准号:
    ST/Y000420/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $11.77万
  • 财政年份:
    2023
  • 负责人:
    Martin Wooster
  • 依托单位:
EO4AgroClimate: How agri-tech and space-based solutions can support climate smart agriculture in Australia
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    ST/W007088/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $3.12万
  • 财政年份:
    2021
  • 负责人:
    Martin Wooster
  • 依托单位:
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    2024
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Incentive and governance schenism study of corporate green washing behavior in China: Based on an integiated view of econfiguration of environmental authority and decoupling logic
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    --
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  • 资助金额:
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Financial Constraints in China and Their Policy Implications
  • 批准号:
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  • 负责人:
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