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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)

基本信息

批准号：
ST/V00137X/1
负责人：
Cunjia Liu
金额：
$ 51.49万
依托单位：
Loughborough University
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
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ST%2FV00137X%2F1
关键词：
Space enabled Crop disEase maNagement

项目摘要

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.

作物病害被广泛认为是现代集约农业的主要挑战之一。它们不仅损害作物产量和品质，对粮食安全构成严重威胁，而且由于过量使用农药的不当和无效处理，对环境产生不利影响。该项目的总体目标是为中国和其他相关国家的主要利益相关者开发和提供交钥匙作物病害管理服务，支持他们对主要作物病害进行早期检测、快速反应和有针对性的干预。这一目标将通过结合之前STFC英国-中国Newton Agritech项目开发的多种作物病害监测和预测技术来实现，并通过与作物喷洒无人机的集成来扩大其影响，以便通过快速，有针对性和自动化的农药喷洒行动来巩固作物病害早期识别和预测的好处。该项目分为六个主要工作包，其中包括四个产品/服务开发工作包，用于开发天基技术并将其转化为农业服务/工具，以及两个示范工作包，用于鼓励接受所开发的服务并向其他国家传播技术。为了促进技术开发/转让，将汇集和利用图像分析方面的最新进展，从遥感数据中提取关键信息（工作方案1）。在动态作物病害管理流程周期之后，该项目将首先开发一项基于云的在线服务，利用作物病害模型、卫星和无人机遥感信息以及环境参数（WP 2）来识别、监测和预测越冬小麦锈病的热点区域。在线服务报告的这些信息可用于通知作物喷洒无人机的规划和部署，以及时控制疾病。其次，为保证农药投放的质量和效果，将开发用于作物喷洒无人机的智能和用户友好的规划和管理软件（WP 4），其中将建立参数化无人机喷洒模型（WP 3）以模拟喷洒存款分布，并进一步开发软件工具以评估不同作物/疾病的喷洒质量。在中国项目合作伙伴的大力支持下，将通过本项目设计的两个示范活动，展示所开发产品/服务的实际效益和长期影响。第一部分（WP 5）研究了甘肃省冬小麦锈病，它是造成华中地区小麦主产区产量损失的病原菌来源。预计利用开发的服务可以有效地识别锈病的热点区域，并在秋季使用喷洒无人机进行处理，从而预防或减少中国其他地区春季锈病流行。第二次宣传活动（WP 6）致力于展示快速应对突发疾病的益处。该软件可根据病害的严重程度和分布情况，以可变速率的方式自动生成喷洒任务，在保证喷洒质量的同时，减少了操作人员的工作量和化学农药和化肥的使用。据设想，该项目将为作物病害管理提供综合农业技术服务，能够提高粮食生产率，降低劳动力和农药成本，并有助于农业的长期可持续增长。此外，通过影响活动，该项目将对中国及其他地区的当地作物保护组织、喷洒服务提供商、无人机操作员以及最终的农民产生深远而持久的影响。