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

(吉隆坡)该项目旨在开发中国病虫害监测、预测和管理的时间序列工具，提供国家和地方层面的服务产品，特别是加强小麦锈病和蝗虫的病虫害防治。它还将开发先进的无人机工具，提供更有效的喷洒控制措施(生物杀虫剂)，以缓解这些问题，而不会造成化学污染。在这种情况下，金的团队将开发方法，将基于卫星的陆地表面温度地图缩小到与农作物生长的田地更相似的比例，以帮助开发可用于预测和监测生物防治措施的有效性和小麦锈病蔓延的数学模型。他们将开发基于无人机的方法，根据航空图像提供作物参数地图，这将用于帮助开发缩小比例的卫星数据集，并提供对作物结构的了解，这些结构可用于帮助开发喷洒技术和将为空中平台开发的规划工具。最后，他们还将开发从热成像遥测蝗虫表面温度的方法，以便为开发更好的蝗虫体内温度模型做出贡献，生物农药开发速度的最终数学模型依赖于此。(拉夫堡)我们的建议旨在通过综合方法来应对这两种主要农业病虫害，发展英国和中国在农业技术方面的长期可持续创新合作伙伴关系。它将从监测、预测和管理的角度出发，结合尖端技术、建模和生物信息。该项目由六个工作包组成，遵循动态农业技术服务的周期：观察以了解问题的性质并定位病虫害/作物问题(WP1)；通过开发预测模型确定方向以提供战略风险意识(WP2)；决定在国家和地方一级提供有用的信息在哪里控制虫害(WP3)；通过无人机部署精确应用生物杀虫剂在当地采取行动(WP4)。该项目的范围主要是农业技术挑战1“精确农业、农业数字化和决策管理工具”，但也对挑战2“提高可持续农业的效率”作出重大贡献。一个关键主题是开发技术，将无人机、地球观测卫星收集的数据和与疾病/虫害建模有关的生物科学应用程序整合在一起。该项目将为农业遥感和植物保护开发自主和智能的规划工具，最终造福于最终用户，以降低成本并提高其业务效率。关键成果之一是开发和应用监测和预测作物病虫害暴发的新技术系统。作为一项新技术，将调查和示范直翅目生物杀虫剂处理，以及对黄锈病和直翅目的建模和预测，实时遥感方法将促进特定时间和特定地点的处理，以及改善一般耕作管理。将这一点与生物杀虫剂方面的工作结合起来，将大大减少化学杀虫剂的使用和作物对化学杀虫剂产生抗药性的风险，并将增加由于缺乏化学杀虫剂而产生的生物多样性。除了这些好处外，该项目还将为英国和中国以外的中国产业合作伙伴开辟新的商机。

(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.