Our network has a growing portfolio of projects which bring together academics and businesses. Our projects explore space enabled technologies in Chinese agriculture including robotic harvesting and grafting; the deployment of UAVs and satellite data; and novel approaches to data handling and modelling. 


Newton Agri-Tech Programme Projects


There are 5 larger projects, in addition to the Agri-Tech in China: Newton Network+ (ATCNN) project, funded under the Newton Agri-Tech Programme:


  •  Enabling Wide Area Persistent Remote Sensing for Agriculture Applications       See summary

  •  Precision Agriculture for Family farms in China (PAFiC)      See summary

  •  Synthesis of remote sensing and novel ground truth sensors to develop high resolution soil moisture monitoring in China and the UK      See summary

  •  Regional crop monitoring and assessment with quantitative remote sensing and data assimilation      See summary

  •  Integrating Advanced Earth Observation and Environmental Information for Sustainable Management of Crop Pests and Diseases      See summary


Projects funded through Agri-Tech in China: Newton Network+ (ATCNN)

The Agri-Tech in China Newton Network has funded a portfolio of 40 projects to stimulate innovation, develop partnerships and test proof of concept ideas. 


Remote Sensing


GIS systems to support in-field manure systems 


Scoping an Information Management System for Chinese Agriculture 

An assessment of the potential of developing frameworks to improve the nutrient use efficiency (NUE) of organic manures at both regional and farm levels in China.
The project will scope an information management system (IMS) for use in Chinese agriculture. Such a system could be used by farmers to help them store their records, track changes in the performance of their crops and make management decisions; by advisors to help them to provide the most appropriate advice and training to farmers; and by researchers to monitor change, analyse cause and effect relationships and develop models. 

A Cloud-based, Mobile-enabled, Data-Driven Approach for Automatic Crop Disease Detection


Applying remote sensing to improve nitrogen use efficiency for potato breeding and commercial production 

Through the joint development of innovative software product, this project will extend and enhance the China CropWatch system with an additional new functionality of crop disease detection to offer viable and sustainable services, thus improving the quality and the yields of crops in China.
The project aims to develop remote sensing tools for non‐destructive high‐throughput phenotyping of potato crops and to use the tools to identify key canopy characteristics associated with increased nitrogen (N) use efficiency and potato yield.

Improving satellite-based models using new satellite data


Assessing the reliability of RS data to predict crop disease

Development of wide-area, frequently-updated map product estimates of soil moisture that could be used to inform an efficient validation process, using investigations into the Sentinel-2 and Sentinel-3 data products in current model parameters and other studies.
Use of mixed modelling and machine learning approaches to assess whether powdery mildew and wheat yield can be predicted by combining data from multiple years, and an examination of the extent to which prediction accuracy depends on year, time within year, flying height, and brand of RS instrument.

Using Sentinel data for drought monitoring


Yield forecasting systems and early blight detection of potato crops

Piloting drought monitoring in Yangling or Inner Mongolia by refining the ESA Sentinel-3 images LST algorithm, and evaluating it against other satellite products, UAV images and ground measurements.
This project aimed to apply the multispectral remote sensing techniques developed in the UK to help with the development of yield forecasting systems and early blight detection of potato crops in China, which will lead to more effective farm management and lower production costs.

Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province


A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation   

This project aims to design a mobile app to provide farmers in STB and Yangxin County with information and advice on their production efficiency performance. 
This project aims to study the feasibility of achieving precise soil management by linking information retrieved from remote sensing and soil/crop models. Water and nutrient dynamics in the soil, as well as associated crop growth will be simulated using the models we have been using with slight modification. 

VIP-STB Farm: Scale up from Village to County/Province Level to STB Programme for Innovation of Chinese Household-Based Small Farms

Taking STBs in Laoling City and Yangxin County, Shandong Province as examples, this project aims to demonstrate feasible solutions for scaling up village-based STBs to upper level. 

UAVs (Unmanned Autonomous Vehicles)


Autonomous vehicle or UAV-mounted sensing systems 


Autonomous vehicle delivery of more precise pesticide application 

An exploration of opportunities to co-develop novel semi-autonomous approaches for rural communities in China
Autonomous safe driving system for agriculture spray machines.

Automated image analysis and processing using UAV-deployed remote sensors 


UAV tracking system for pollinators 

Development of an automated image analysis solution to identify key wheat growth stages based on large aerial images.
Validation of the effectiveness of a novel tracking device for insect pollinators across their entire foraging range.

Diagnosis, data assimilation and decision-making systems for precision management of water and nitrogen in the Southern China 



This project aims to develop a tool that can predict and diagnose cropresponse to water and nutrient related limits. This knowledge will guide crop management and help to inform stakeholders from across the arable supply chain about the best approaches for land management towards more sustainable and efficient production, using precision agriculture.

Drones and Robotics


China Robot Harvest


   Space Robotic Technologies for Plant Grafting

This project intends to work towards the exchange of robotics technology for the safe and efficient harvest of fruits and vegetable crops grown in glasshouses and plastic tunnels.
The project aims to gain better scientific understanding of grafting process for Chinese farmers, then develop a cost effective and efficient grafting robotic system by exploiting space robotic technologies available within the consortium. 

China Robot Harvest++


Highly Efficient Intelligent Irrigation Systems

This project aims to develop and commercialise soft robotics for automated harvesting of protected crops. In the first instance, it will continue development of a robotic system for tomato picking suitable for the Chinese market
To develop highly efficient intelligent irrigation systems by integrating all these latest technologies in a systematic way and, with the support of Chinese partner Jiangsu University, to prove the concept and investigate the feasibility of the proposed intelligent irrigation system with particular attention in its applications in the north part of China.

Feasibility Study of a Self-Propelled Capsule Robot for Irrigation Pipeline Inspection



This project aimed to carry out a feasibility study of using a self-propelled vibro-impact capsule robot for irrigation pipeline inspection in rural China.

General Agri-Tech


Translating UK expertise in viticulture weather risk analysis into sustainable vineyard management tools for vineyards in China


How internet of things technologies can transform  after-sales services and improve machine manufacturers efficiency

This project aims to assess the potential for, and advantages of automated and remote environmental data capture as vineyard management tools. 
This project will examine the potential of utilizing internet of things for detection, transferring, storage and analysis of a variety of condition data and aims to trigger a mobile application to support effective and timely fault diagnoisis, and high-quality remote customer training.

Management zone delineation and decision support system for small scale farming at village level in North China Plain


NeWMap: Enhanced farm-specific NutriEnt and Water stress Maps

A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei).
This project aims to address the challenge that there is a need of field-specific advice for small-scale farming in China. It aims to integrate UAV data and field-specific and local environment data collected from small-scale farms to automatically provide a nutrient assessment map and a water stress map.



Data innovations and sustainability in agri-food supply chains: Evidence from Henan Province, China


Wheat Rust and Wheat Growth Modelling Workshop

To hold a workshop with UK experts in the field of big data and agriculture sustainability and representatives from the Chinese agri-food sector and academics. The workshop will assess current practices in China on data innovations in the agri-food industry, learn from best practice examples from the UK and identify opportunities for further collaboration between Chinese and UK partners.
To hold a two-day workshop with leading experts on wheat rust and wheat growth modelling and earth observation.

Radar and Aerial Ecology Summer School 

To build on current work operating and ground-truthing a vertical-looking entomological radar (VLR) and to convene a two-week Summer School, teaching and practising techniques involved in operating and ground-truthing a vertical-looking entomological radar (VLR).