Agri-Tech in China Network+
Lead Research Organisation:
Rothamsted Research
Abstract
The great majority of China's farms are smallholder properties with insufficient productivity to support farmers in rural communities on their own. Agriculture on these properties is threatened by a number of forces including soil degradation, pollution of soils and chemical residues in crop plants, unsustainable water use and polluted water, and inefficient use of inputs. The UK, through programmes like Newton Network+, will invest tens of millions of pounds over the next few years helping China progress to smarter and more sustainable agricultural systems - ensuring its food security, while opening up huge opportunities for economic growth.
Firstly, this Network+ will ensure the effective coordination of these initiatives, and that the different projects link together to strengthen each other. It will do this by undertaking a wide range of networking and engagement activities to link researchers and businesses in China and the UK to ensure maximum possible knowledge sharing and new project development.
Secondly, the Network+ will support a pipeline of innovation through the funding of feasibility studies and around 35 proof of concept and feasibility projects to develop pathways to new solutions to the challenges outlined above. Finally, up to 3 of the proof of concept projects will be selected for development into full-scale projects that will result in solutions on the ground to help support economic growth and development in rural communities in China.
Finally, the Network+ will support a wide range of dissemination events to ensure that knowledge generated from STFC projects, as well as new results from across the agritech sector, is shared across the community.
Firstly, this Network+ will ensure the effective coordination of these initiatives, and that the different projects link together to strengthen each other. It will do this by undertaking a wide range of networking and engagement activities to link researchers and businesses in China and the UK to ensure maximum possible knowledge sharing and new project development.
Secondly, the Network+ will support a pipeline of innovation through the funding of feasibility studies and around 35 proof of concept and feasibility projects to develop pathways to new solutions to the challenges outlined above. Finally, up to 3 of the proof of concept projects will be selected for development into full-scale projects that will result in solutions on the ground to help support economic growth and development in rural communities in China.
Finally, the Network+ will support a wide range of dissemination events to ensure that knowledge generated from STFC projects, as well as new results from across the agritech sector, is shared across the community.
Planned Impact
The Agri-Tech in China Network+ will contribute to the overall goal of Newton Fund Agri-Tech in China programme on promoting sustainable intensification of agriculture and rural income in China.
Sustainable intensification of China's agriculture face many challenges. From a technical point of view, it is important to protect the natural resource base, raise productivity and resource use efficiency, and at the meantime to reduce non-point and point source pollution. From a socio-economic and institutional point of view, in order to efficiently implement the new sustainable agriculture plan (2015-2030), there is need to foster structural change in the agricultural sector, support Agri-Tech uptake and application by farmers, improve delivery mechanisms to inform farmers and other users of Agri-Tech, and to address the rising cost of agricultural labour.
The Newton Fund Agri-Tech in China programme will address the above challenges through application and adaptation of UK remote sensing and modelling technologies into China's agriculture production system. This will be achieved through implantation of a number of projects around the themes of sustainable intensification, pests and diseases management, climate smart agriculture, precision agriculture technologies, as well as development of the enabling technologies.
The Network+ will support the implementation of the Agri-Tech in China programme through:
(i) Working with and build on existing and planned initiatives and foster new partnerships
(ii) Facilitating effective communication between Network+ members and build up synergies between STFC and Network+ funded projects, through innovative mechanisms (e.g. a mutual learning platform);
(iii) Engaging with stakeholder communities including farmers, policy makers, business and academic communities;
(iv) Developing communication and dissemination tools for knowledge sharing and transfer, such as policy briefs, position papers, synthesis reports, and workshops.
To make all Network+ activities better coordinated and to build up synergies between them, the activities will be grouped into four portfolios (this does not mean these activities will be isolated from each other):
Portfolio 1 will focus on people exchange aimed at capacity building and the establishment of long-term partnerships. Activities will include visits, placements, and short training courses;
Portfolio 2 will focus on small scale research projects, including scoping studies and POC studies;
Portfolio 3 will focus on knowledge sharing and transfer, aiming to engage broadly with stakeholders and disseminate/communicate outputs.
Portfolio 4 will create a technology transfer and commercialisation platform to enable the innovations and intellectual property developed during the course of the Newton programme to be protected and commercialised to promote economic growth in rural China.
Sustainable intensification of China's agriculture face many challenges. From a technical point of view, it is important to protect the natural resource base, raise productivity and resource use efficiency, and at the meantime to reduce non-point and point source pollution. From a socio-economic and institutional point of view, in order to efficiently implement the new sustainable agriculture plan (2015-2030), there is need to foster structural change in the agricultural sector, support Agri-Tech uptake and application by farmers, improve delivery mechanisms to inform farmers and other users of Agri-Tech, and to address the rising cost of agricultural labour.
The Newton Fund Agri-Tech in China programme will address the above challenges through application and adaptation of UK remote sensing and modelling technologies into China's agriculture production system. This will be achieved through implantation of a number of projects around the themes of sustainable intensification, pests and diseases management, climate smart agriculture, precision agriculture technologies, as well as development of the enabling technologies.
The Network+ will support the implementation of the Agri-Tech in China programme through:
(i) Working with and build on existing and planned initiatives and foster new partnerships
(ii) Facilitating effective communication between Network+ members and build up synergies between STFC and Network+ funded projects, through innovative mechanisms (e.g. a mutual learning platform);
(iii) Engaging with stakeholder communities including farmers, policy makers, business and academic communities;
(iv) Developing communication and dissemination tools for knowledge sharing and transfer, such as policy briefs, position papers, synthesis reports, and workshops.
To make all Network+ activities better coordinated and to build up synergies between them, the activities will be grouped into four portfolios (this does not mean these activities will be isolated from each other):
Portfolio 1 will focus on people exchange aimed at capacity building and the establishment of long-term partnerships. Activities will include visits, placements, and short training courses;
Portfolio 2 will focus on small scale research projects, including scoping studies and POC studies;
Portfolio 3 will focus on knowledge sharing and transfer, aiming to engage broadly with stakeholders and disseminate/communicate outputs.
Portfolio 4 will create a technology transfer and commercialisation platform to enable the innovations and intellectual property developed during the course of the Newton programme to be protected and commercialised to promote economic growth in rural China.
Organisations
- Rothamsted Research (Lead Research Organisation)
- James Hutton Institute (Collaboration)
- Manchester University (Collaboration)
- IBM (Collaboration)
- Liverpool John Moores University (Collaboration)
- China Academy of Launch Vehicle Technology (Collaboration)
- Microsoft Research (Collaboration)
- University of Reading (Collaboration)
- AgSpace Agriculture Ltd (Collaboration)
- Nanjing Agricultural University (Collaboration)
- ECOMETRICA LTD (Collaboration)
- UNIVERSITY OF STRATHCLYDE (Collaboration)
- Henan University (Collaboration)
- Wuhan University (Collaboration)
- Taiyuan University of Technology (Collaboration)
- Yu Long Machinery Ltd (Collaboration)
- CRANFIELD UNIVERSITY (Collaboration)
- University of Leicester (Collaboration)
- China Centre for Resources Satellite Data and Application (Collaboration)
- Bangor University (Collaboration)
- Centre for Agriculture and Bioscience International (Collaboration)
- BASF (Collaboration)
- Climate Wine Consulting Ltd (Collaboration)
- National Institute of Agricultural Botany (Collaboration)
- GSMA (Collaboration)
- University of East Anglia (Collaboration)
- UNIVERSITY OF EXETER (Collaboration)
- Chinese Academy of Agricultural Sciences (Collaboration)
- Academy of Sciences of the Czech Republic (Collaboration)
- Syngenta International AG (Collaboration)
- Chinese Academy of Sciences (Collaboration)
- Courtyard Agriculture Ltd (Collaboration)
- Henan Agricultural University (Collaboration)
- Jiangsu University (Collaboration)
- Fieldwork Robotics Limited (Collaboration)
- EARLHAM INSTITUTE (Collaboration)
- Agricultural University of Hebei (Collaboration)
- De Tao Group (Collaboration)
- Shanghai Jiao Tong University (Collaboration)
- ABERYSTWYTH UNIVERSITY (Collaboration)
- China Agricultural University (CAU) (Collaboration)
- Carbon Trust (Collaboration)
- Agrimetrics Ltd (Collaboration)
- Henan University of Science and Technology (Collaboration)
- Shandong Agricultural University (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- Roehampton University (Collaboration)
- Loughborough University (Collaboration)
- Rothamsted Research (Collaboration)
- Yancheng Teachers University (Collaboration)
- Keele University (Collaboration)
- Velcourt Ltd (Collaboration)
- University College London (Collaboration)
- University of Electronic Science and Technology of China (UESTC) (Collaboration)
- University of Manchester (Collaboration)
- University of Newcastle (Collaboration)
- Xisen Potato Industry Group Ltd (Collaboration)
- Scotland's Rural College (Collaboration)
- Assimila Ltd (Collaboration)
- MANCHESTER METROPOLITAN UNIVERSITY (Collaboration)
- Peking University (Collaboration)
- North West Agriculture and Forestry University (Collaboration)
- University of Plymouth (Collaboration)
- Mapping Earth Resources Ltd (Collaboration)
- UNIVERSITY OF BEDFORDSHIRE (Collaboration)
- RSK ADAS Ltd (Collaboration)
- Map of Agriculture Limited (Collaboration)
- UNIVERSITY OF KENT (Collaboration)
- National Institute of Agronomy and Botany (NIAB) (Collaboration)
Publications
Dällenbach L
(2018)
Higher flight activity in the offspring of migrants compared to residents in a migratory insect
in Proceedings of the Royal Society B: Biological Sciences
Liu W
(2018)
Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography.
in Plant disease
Yan Y
(2017)
A comparative study of the vibro-impact capsule systems with one-sided and two-sided constraints.
in Nonlinear dynamics
Yan Y
(2018)
Proof-of-concept prototype development of the self-propelled capsule system for pipeline inspection.
in Meccanica
Yan Y
(2018)
Optimization and experimental verification of the vibro-impact capsule system in fluid pipeline
in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
| Description | Presentation to OECD Global Forum on Agriculture, Paris 2018 on role of policy in the future of agriculture innovation |
| Geographic Reach | Europe |
| Policy Influence Type | Participation in a guidance/advisory committee |
| Description | "China Robot Harvest" (Proof-of-Concept Award: PC014) |
| Organisation | De Tao Group |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Wenhua Sun and Zhonglin Zhang (Sunqiao), Yuanfei Zhou (Shanghai Jiaotong University) Project start date: 1 May 2017 Duration: Four months Project Summary: This project aimed 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. |
| Collaborator Contribution | University of Plymouth: existing robot hardware and computing hardware and parallel processing facilities De Tao: travel and subsistence costs for Prof Fuller to visit China Sunqiao: crop production resources for experimental work at Sunqiao Agricultural Park Shanghai Jiaotong University: crop production resources for experimental work at Pujiang Green Valley Experimental Station |
| Impact | The final platform was showcased during a very successful demonstration in Shanghai with all project partners, and Chinese funding authorities. We aim to continue this successful project with further development and testing. The project received further funding from Agri-Tech in China Network+. |
| Start Year | 2017 |
| Description | "China Robot Harvest" (Proof-of-Concept Award: PC014) |
| Organisation | Fieldwork Robotics Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Wenhua Sun and Zhonglin Zhang (Sunqiao), Yuanfei Zhou (Shanghai Jiaotong University) Project start date: 1 May 2017 Duration: Four months Project Summary: This project aimed 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. |
| Collaborator Contribution | University of Plymouth: existing robot hardware and computing hardware and parallel processing facilities De Tao: travel and subsistence costs for Prof Fuller to visit China Sunqiao: crop production resources for experimental work at Sunqiao Agricultural Park Shanghai Jiaotong University: crop production resources for experimental work at Pujiang Green Valley Experimental Station |
| Impact | The final platform was showcased during a very successful demonstration in Shanghai with all project partners, and Chinese funding authorities. We aim to continue this successful project with further development and testing. The project received further funding from Agri-Tech in China Network+. |
| Start Year | 2017 |
| Description | "China Robot Harvest" (Proof-of-Concept Award: PC014) |
| Organisation | Shanghai Jiao Tong University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Wenhua Sun and Zhonglin Zhang (Sunqiao), Yuanfei Zhou (Shanghai Jiaotong University) Project start date: 1 May 2017 Duration: Four months Project Summary: This project aimed 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. |
| Collaborator Contribution | University of Plymouth: existing robot hardware and computing hardware and parallel processing facilities De Tao: travel and subsistence costs for Prof Fuller to visit China Sunqiao: crop production resources for experimental work at Sunqiao Agricultural Park Shanghai Jiaotong University: crop production resources for experimental work at Pujiang Green Valley Experimental Station |
| Impact | The final platform was showcased during a very successful demonstration in Shanghai with all project partners, and Chinese funding authorities. We aim to continue this successful project with further development and testing. The project received further funding from Agri-Tech in China Network+. |
| Start Year | 2017 |
| Description | "China Robot Harvest" (Proof-of-Concept Award: PC014) |
| Organisation | University of Plymouth |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Wenhua Sun and Zhonglin Zhang (Sunqiao), Yuanfei Zhou (Shanghai Jiaotong University) Project start date: 1 May 2017 Duration: Four months Project Summary: This project aimed 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. |
| Collaborator Contribution | University of Plymouth: existing robot hardware and computing hardware and parallel processing facilities De Tao: travel and subsistence costs for Prof Fuller to visit China Sunqiao: crop production resources for experimental work at Sunqiao Agricultural Park Shanghai Jiaotong University: crop production resources for experimental work at Pujiang Green Valley Experimental Station |
| Impact | The final platform was showcased during a very successful demonstration in Shanghai with all project partners, and Chinese funding authorities. We aim to continue this successful project with further development and testing. The project received further funding from Agri-Tech in China Network+. |
| Start Year | 2017 |
| Description | A Cloud-based, Mobile-enabled, Data-Driven Approach for Automatic Crop Disease Detection (Proof-of-Concept Award: PC006) |
| Organisation | Chinese Academy of Sciences |
| Country | China |
| Sector | Public |
| PI Contribution | Project Lead(s): Prof. Liangxiu Han (Manchester Metropolitan University) Project Members: Prof. Bingfang Wu and Dr. Sheng Chang, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Science (CAS) Project start date: 1 April 2017 Duration: Four months Project Summary: The main aim of this project was to develop a novel automated big-data driven approach for crop disease detection to provide a rapidly reliable service to minimise the risk of crop loss from diseases in China. |
| Collaborator Contribution | Access to the big data computing platform and expertise and skills of MMU Crime and Big Data Centre. Costs for 2 Chinese researchers to travel to/within the UK. Staff/Technical support: 2 months data collection and Integration with CropWatch system |
| Impact | We have developed a cloud-based, mobile enabled, data driven diagnostic tool for automatic crop disease detection. Currently, it is a demonstrable, working prototype. Two versions in both Chinese and English have been developed, which can be used in both China and UK. It can be easily to extend to detect other crop diseases, if we were provided more funding and time. We have created product videos for disseminations (the first one below). We have also created prototype demos (the second and third ones) 1) Crop disease detector video production: https://youtu.be/IDTOd4G4rhA 2) Crop disease demo video in Chinese: https://youtu.be/DgDCo_iBGIU 3) Crop disease demo video in English: https://youtu.be/J0r6tVJJ7wA Workshop: "Precision Agriculture: Data-Driven Approach to Crop Monitoring and Disease Diagnosis" at Manchester Metropolitan University 31 August, 2017 (http://precision-agriculture.eventbrite.co.uk) Keynote speaker: International workshop on "Advanced Topics in Computing Technology and Applications", in conjunction with the 10th IEEE International Conference on Cyber, Physical, and Social Computing (CPSCom-2017), 21-23, June, Exter 2017. The talk tile is "Large-scale Data Processing and Data Analytics on Images". Keynote speech: International Conference on Future Networks and Distributed Systems (ICFNDS) (http://www.icfnds.org) in July 2017, Cambridge. "Towards Sustainable Smart Society: Big Data Driven Approaches". (http://dl.acm.org/citation.cfm?id=3102307&CFID=812199929&CFTO KEN=33054438. |
| Start Year | 2017 |
| Description | A Cloud-based, Mobile-enabled, Data-Driven Approach for Automatic Crop Disease Detection (Proof-of-Concept Award: PC006) |
| Organisation | Manchester Metropolitan University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof. Liangxiu Han (Manchester Metropolitan University) Project Members: Prof. Bingfang Wu and Dr. Sheng Chang, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Science (CAS) Project start date: 1 April 2017 Duration: Four months Project Summary: The main aim of this project was to develop a novel automated big-data driven approach for crop disease detection to provide a rapidly reliable service to minimise the risk of crop loss from diseases in China. |
| Collaborator Contribution | Access to the big data computing platform and expertise and skills of MMU Crime and Big Data Centre. Costs for 2 Chinese researchers to travel to/within the UK. Staff/Technical support: 2 months data collection and Integration with CropWatch system |
| Impact | We have developed a cloud-based, mobile enabled, data driven diagnostic tool for automatic crop disease detection. Currently, it is a demonstrable, working prototype. Two versions in both Chinese and English have been developed, which can be used in both China and UK. It can be easily to extend to detect other crop diseases, if we were provided more funding and time. We have created product videos for disseminations (the first one below). We have also created prototype demos (the second and third ones) 1) Crop disease detector video production: https://youtu.be/IDTOd4G4rhA 2) Crop disease demo video in Chinese: https://youtu.be/DgDCo_iBGIU 3) Crop disease demo video in English: https://youtu.be/J0r6tVJJ7wA Workshop: "Precision Agriculture: Data-Driven Approach to Crop Monitoring and Disease Diagnosis" at Manchester Metropolitan University 31 August, 2017 (http://precision-agriculture.eventbrite.co.uk) Keynote speaker: International workshop on "Advanced Topics in Computing Technology and Applications", in conjunction with the 10th IEEE International Conference on Cyber, Physical, and Social Computing (CPSCom-2017), 21-23, June, Exter 2017. The talk tile is "Large-scale Data Processing and Data Analytics on Images". Keynote speech: International Conference on Future Networks and Distributed Systems (ICFNDS) (http://www.icfnds.org) in July 2017, Cambridge. "Towards Sustainable Smart Society: Big Data Driven Approaches". (http://dl.acm.org/citation.cfm?id=3102307&CFID=812199929&CFTO KEN=33054438. |
| Start Year | 2017 |
| Description | A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation: feasibility study (WK009) |
| Organisation | Chinese Academy of Agricultural Sciences |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Xiaoxian Zhang (Rothamsted Research) Project Members: Dr Yuanyuan Zha (Wuhan University), Dr. Ben Zhao and Qibiao Han (Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences), Yanan Zhao (Henan Agricultural University) Project start date: 1 April 2018 Duration: 10 months Project Summary: Previously funded Network+ projects have made progress in using remote sensing to diagnose water and nutrients in canopy, but applying them to the STB fields needs extra work because it is water and nutrients in soil that need management. While nutrient in canopy is controlled by nutrients in soil, they are not proportional. Uptake of nutrients by plant depends on their bioavailability rather than their absolute contents. Managing soil nutrients based on their contents in canopy is an improvement, but precise management is not achievable unless their dynamics in root-zone soil is known. This project aims to study the feasibility of achieving this by linking information retrieved from remote sensing and soil/crop model. |
| Collaborator Contribution | Chinese partners will work on the project for free and there are not indirect costs from their employer. In addition, most Chinese teams will provide their equipment, remote sensing images, computing facility (Wuhan University) free of charge to the project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation: feasibility study (WK009) |
| Organisation | Henan Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Xiaoxian Zhang (Rothamsted Research) Project Members: Dr Yuanyuan Zha (Wuhan University), Dr. Ben Zhao and Qibiao Han (Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences), Yanan Zhao (Henan Agricultural University) Project start date: 1 April 2018 Duration: 10 months Project Summary: Previously funded Network+ projects have made progress in using remote sensing to diagnose water and nutrients in canopy, but applying them to the STB fields needs extra work because it is water and nutrients in soil that need management. While nutrient in canopy is controlled by nutrients in soil, they are not proportional. Uptake of nutrients by plant depends on their bioavailability rather than their absolute contents. Managing soil nutrients based on their contents in canopy is an improvement, but precise management is not achievable unless their dynamics in root-zone soil is known. This project aims to study the feasibility of achieving this by linking information retrieved from remote sensing and soil/crop model. |
| Collaborator Contribution | Chinese partners will work on the project for free and there are not indirect costs from their employer. In addition, most Chinese teams will provide their equipment, remote sensing images, computing facility (Wuhan University) free of charge to the project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation: feasibility study (WK009) |
| Organisation | Rothamsted Research |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Xiaoxian Zhang (Rothamsted Research) Project Members: Dr Yuanyuan Zha (Wuhan University), Dr. Ben Zhao and Qibiao Han (Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences), Yanan Zhao (Henan Agricultural University) Project start date: 1 April 2018 Duration: 10 months Project Summary: Previously funded Network+ projects have made progress in using remote sensing to diagnose water and nutrients in canopy, but applying them to the STB fields needs extra work because it is water and nutrients in soil that need management. While nutrient in canopy is controlled by nutrients in soil, they are not proportional. Uptake of nutrients by plant depends on their bioavailability rather than their absolute contents. Managing soil nutrients based on their contents in canopy is an improvement, but precise management is not achievable unless their dynamics in root-zone soil is known. This project aims to study the feasibility of achieving this by linking information retrieved from remote sensing and soil/crop model. |
| Collaborator Contribution | Chinese partners will work on the project for free and there are not indirect costs from their employer. In addition, most Chinese teams will provide their equipment, remote sensing images, computing facility (Wuhan University) free of charge to the project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | A roadmap to improve precise soil management by linking crop modelling and remote sensing images via data assimilation: feasibility study (WK009) |
| Organisation | Wuhan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Xiaoxian Zhang (Rothamsted Research) Project Members: Dr Yuanyuan Zha (Wuhan University), Dr. Ben Zhao and Qibiao Han (Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences), Yanan Zhao (Henan Agricultural University) Project start date: 1 April 2018 Duration: 10 months Project Summary: Previously funded Network+ projects have made progress in using remote sensing to diagnose water and nutrients in canopy, but applying them to the STB fields needs extra work because it is water and nutrients in soil that need management. While nutrient in canopy is controlled by nutrients in soil, they are not proportional. Uptake of nutrients by plant depends on their bioavailability rather than their absolute contents. Managing soil nutrients based on their contents in canopy is an improvement, but precise management is not achievable unless their dynamics in root-zone soil is known. This project aims to study the feasibility of achieving this by linking information retrieved from remote sensing and soil/crop model. |
| Collaborator Contribution | Chinese partners will work on the project for free and there are not indirect costs from their employer. In addition, most Chinese teams will provide their equipment, remote sensing images, computing facility (Wuhan University) free of charge to the project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province (WK006) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Francisco Areal (University of Reading) Project Members: Prof Wantao Yu (University of Roehampton), Zhigang Liu (Courtyard Agriculture Ltd), Prof Kevin Tansey (University of Leicester), Dr Chunlin Yuan (Henan University), Jiahuan Liu (China Agricultural University) Project start date: 1 Aug 2018 Duration: 8 months Project Summary: This project will design a mobile app based on farmers requirements to provide farmers in STB (Science and Technology Backyards) and Yangxin County with information and advice on their production efficiency performance. |
| Collaborator Contribution | University of Reading and University of Roehampton will allow full use of its facilities for members of the project team including the booking of meeting rooms, access to libraries, online catalogues and office spaces. University of Reading and University of Roehampton will also make its information technology infrastructure available for the project, including secure file transfer/sharing, storage space on the university severs and international communications facilities. Henan University and China Agricultural University will bear staff costs of their staff members. Henan University and China Agricultural University will offer help and resources to support the data collection process in STB and Yangxin County, China, and to disseminate the outcomes of the project to the community using a variety of social media tools. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province (WK006) |
| Organisation | Courtyard Agriculture Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Francisco Areal (University of Reading) Project Members: Prof Wantao Yu (University of Roehampton), Zhigang Liu (Courtyard Agriculture Ltd), Prof Kevin Tansey (University of Leicester), Dr Chunlin Yuan (Henan University), Jiahuan Liu (China Agricultural University) Project start date: 1 Aug 2018 Duration: 8 months Project Summary: This project will design a mobile app based on farmers requirements to provide farmers in STB (Science and Technology Backyards) and Yangxin County with information and advice on their production efficiency performance. |
| Collaborator Contribution | University of Reading and University of Roehampton will allow full use of its facilities for members of the project team including the booking of meeting rooms, access to libraries, online catalogues and office spaces. University of Reading and University of Roehampton will also make its information technology infrastructure available for the project, including secure file transfer/sharing, storage space on the university severs and international communications facilities. Henan University and China Agricultural University will bear staff costs of their staff members. Henan University and China Agricultural University will offer help and resources to support the data collection process in STB and Yangxin County, China, and to disseminate the outcomes of the project to the community using a variety of social media tools. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province (WK006) |
| Organisation | Henan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Francisco Areal (University of Reading) Project Members: Prof Wantao Yu (University of Roehampton), Zhigang Liu (Courtyard Agriculture Ltd), Prof Kevin Tansey (University of Leicester), Dr Chunlin Yuan (Henan University), Jiahuan Liu (China Agricultural University) Project start date: 1 Aug 2018 Duration: 8 months Project Summary: This project will design a mobile app based on farmers requirements to provide farmers in STB (Science and Technology Backyards) and Yangxin County with information and advice on their production efficiency performance. |
| Collaborator Contribution | University of Reading and University of Roehampton will allow full use of its facilities for members of the project team including the booking of meeting rooms, access to libraries, online catalogues and office spaces. University of Reading and University of Roehampton will also make its information technology infrastructure available for the project, including secure file transfer/sharing, storage space on the university severs and international communications facilities. Henan University and China Agricultural University will bear staff costs of their staff members. Henan University and China Agricultural University will offer help and resources to support the data collection process in STB and Yangxin County, China, and to disseminate the outcomes of the project to the community using a variety of social media tools. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province (WK006) |
| Organisation | Roehampton University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Francisco Areal (University of Reading) Project Members: Prof Wantao Yu (University of Roehampton), Zhigang Liu (Courtyard Agriculture Ltd), Prof Kevin Tansey (University of Leicester), Dr Chunlin Yuan (Henan University), Jiahuan Liu (China Agricultural University) Project start date: 1 Aug 2018 Duration: 8 months Project Summary: This project will design a mobile app based on farmers requirements to provide farmers in STB (Science and Technology Backyards) and Yangxin County with information and advice on their production efficiency performance. |
| Collaborator Contribution | University of Reading and University of Roehampton will allow full use of its facilities for members of the project team including the booking of meeting rooms, access to libraries, online catalogues and office spaces. University of Reading and University of Roehampton will also make its information technology infrastructure available for the project, including secure file transfer/sharing, storage space on the university severs and international communications facilities. Henan University and China Agricultural University will bear staff costs of their staff members. Henan University and China Agricultural University will offer help and resources to support the data collection process in STB and Yangxin County, China, and to disseminate the outcomes of the project to the community using a variety of social media tools. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Achieving Sustainable Intensification using Remote Sensing: Evidence from STB and Yangxin County, Shandong Province (WK006) |
| Organisation | University of Reading |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Francisco Areal (University of Reading) Project Members: Prof Wantao Yu (University of Roehampton), Zhigang Liu (Courtyard Agriculture Ltd), Prof Kevin Tansey (University of Leicester), Dr Chunlin Yuan (Henan University), Jiahuan Liu (China Agricultural University) Project start date: 1 Aug 2018 Duration: 8 months Project Summary: This project will design a mobile app based on farmers requirements to provide farmers in STB (Science and Technology Backyards) and Yangxin County with information and advice on their production efficiency performance. |
| Collaborator Contribution | University of Reading and University of Roehampton will allow full use of its facilities for members of the project team including the booking of meeting rooms, access to libraries, online catalogues and office spaces. University of Reading and University of Roehampton will also make its information technology infrastructure available for the project, including secure file transfer/sharing, storage space on the university severs and international communications facilities. Henan University and China Agricultural University will bear staff costs of their staff members. Henan University and China Agricultural University will offer help and resources to support the data collection process in STB and Yangxin County, China, and to disseminate the outcomes of the project to the community using a variety of social media tools. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | An exploration of how the internet of things technologies can transform the after-sales services and improve the efficiency of machine manufacturers in China (Pathfinder Award: PF005) |
| Organisation | Liverpool John Moores University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Po Yang (Liverpool John Moores University) Project Members: Dr. Lei Wang (Yu Long Machinery Ltd) Project start date: 1 August 2017 Duration: One month Project Summary: This project examined the potential of utilizing internet of things for detection, transferring, storage and analysis of a variety of condition data. The aim was to trigger a mobile application to support effective and timely fault diagnoisis, and high-quality remote customer training. |
| Collaborator Contribution | The project will receive a strong support from Yulong Machinery Ltd in China, and its associated stakeholders. On April 2016, Yulong Machinary Ltd has successful granted a investment 30 million RMB from a IPO organisation in China: Xingguang Agricultural Machinery Co. Ltd. This grant will ensure the expansion and continuity of machines production of Yulong Machinery Ltd. Also, Yulong machinery Ltd has recently certificated as China High Technology Enterprise and Hubei Province Agricultural Mechanisation Leading Enterprise by Central and Local government. These proofs will guarantee the obtaining of policy support to Yulong machinary Ltd in the next few years. Those benefits will give powerful support to success of this project, including high quality survey of user requirement analysis and economic efficiency evaluation. |
| Impact | The PI gave 2 talks in top research intuitions in China: Institution of Intelligent Mechanics, CAS and Wuhan University. It will lead to the establishment of long-term research links with a wide range of China academic and industrial partners for enhancing the exploration and dissemination in my research ideas. 1 conference paper and 1 journal paper with our project partners. Also, we have already produced a special issue proposal in Applied Science (Impact Factor: 1.73), which is about Advanced Internet of Things for Smart Infrastructure. The PI is the chief guest-editor of this special issue. |
| Start Year | 2017 |
| Description | An exploration of how the internet of things technologies can transform the after-sales services and improve the efficiency of machine manufacturers in China (Pathfinder Award: PF005) |
| Organisation | Yu Long Machinery Ltd |
| Country | China |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Po Yang (Liverpool John Moores University) Project Members: Dr. Lei Wang (Yu Long Machinery Ltd) Project start date: 1 August 2017 Duration: One month Project Summary: This project examined the potential of utilizing internet of things for detection, transferring, storage and analysis of a variety of condition data. The aim was to trigger a mobile application to support effective and timely fault diagnoisis, and high-quality remote customer training. |
| Collaborator Contribution | The project will receive a strong support from Yulong Machinery Ltd in China, and its associated stakeholders. On April 2016, Yulong Machinary Ltd has successful granted a investment 30 million RMB from a IPO organisation in China: Xingguang Agricultural Machinery Co. Ltd. This grant will ensure the expansion and continuity of machines production of Yulong Machinery Ltd. Also, Yulong machinery Ltd has recently certificated as China High Technology Enterprise and Hubei Province Agricultural Mechanisation Leading Enterprise by Central and Local government. These proofs will guarantee the obtaining of policy support to Yulong machinary Ltd in the next few years. Those benefits will give powerful support to success of this project, including high quality survey of user requirement analysis and economic efficiency evaluation. |
| Impact | The PI gave 2 talks in top research intuitions in China: Institution of Intelligent Mechanics, CAS and Wuhan University. It will lead to the establishment of long-term research links with a wide range of China academic and industrial partners for enhancing the exploration and dissemination in my research ideas. 1 conference paper and 1 journal paper with our project partners. Also, we have already produced a special issue proposal in Applied Science (Impact Factor: 1.73), which is about Advanced Internet of Things for Smart Infrastructure. The PI is the chief guest-editor of this special issue. |
| Start Year | 2017 |
| Description | Applying remote sensing to improve nitrogen use efficiency for potato breeding and commercial production (Large Project Award: LG005) |
| Organisation | Aberystwyth University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof. Xiangming Xu (NIAB EMR) Project Members: Dr. Bo Li (NIAB), Dr. Jiwan Han (Aberystwyth University), Dr. Jiangang Liu and Prof. Liping Jin (Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences), Dr. Baigeng Hu (Xisen Potato Industry Group Ltd) Project start date: 1 April 2018 Duration: 10 months Project Summary: This 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. |
| Collaborator Contribution | Institute of Vegetables and Flowers, CAAS: Staff cost for 30 days, consumables and plant material for the potato field experiment Xisen Potato Group: Three days staff cost for consultants of Chinese potato growing and market exploitation |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Applying remote sensing to improve nitrogen use efficiency for potato breeding and commercial production (Large Project Award: LG005) |
| Organisation | Chinese Academy of Agricultural Sciences |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof. Xiangming Xu (NIAB EMR) Project Members: Dr. Bo Li (NIAB), Dr. Jiwan Han (Aberystwyth University), Dr. Jiangang Liu and Prof. Liping Jin (Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences), Dr. Baigeng Hu (Xisen Potato Industry Group Ltd) Project start date: 1 April 2018 Duration: 10 months Project Summary: This 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. |
| Collaborator Contribution | Institute of Vegetables and Flowers, CAAS: Staff cost for 30 days, consumables and plant material for the potato field experiment Xisen Potato Group: Three days staff cost for consultants of Chinese potato growing and market exploitation |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Applying remote sensing to improve nitrogen use efficiency for potato breeding and commercial production (Large Project Award: LG005) |
| Organisation | National Institute Of Agricultural Botany |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Prof. Xiangming Xu (NIAB EMR) Project Members: Dr. Bo Li (NIAB), Dr. Jiwan Han (Aberystwyth University), Dr. Jiangang Liu and Prof. Liping Jin (Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences), Dr. Baigeng Hu (Xisen Potato Industry Group Ltd) Project start date: 1 April 2018 Duration: 10 months Project Summary: This 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. |
| Collaborator Contribution | Institute of Vegetables and Flowers, CAAS: Staff cost for 30 days, consumables and plant material for the potato field experiment Xisen Potato Group: Three days staff cost for consultants of Chinese potato growing and market exploitation |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Applying remote sensing to improve nitrogen use efficiency for potato breeding and commercial production (Large Project Award: LG005) |
| Organisation | Xisen Potato Industry Group Ltd |
| Country | China |
| Sector | Private |
| PI Contribution | Project Lead(s): Prof. Xiangming Xu (NIAB EMR) Project Members: Dr. Bo Li (NIAB), Dr. Jiwan Han (Aberystwyth University), Dr. Jiangang Liu and Prof. Liping Jin (Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences), Dr. Baigeng Hu (Xisen Potato Industry Group Ltd) Project start date: 1 April 2018 Duration: 10 months Project Summary: This 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. |
| Collaborator Contribution | Institute of Vegetables and Flowers, CAAS: Staff cost for 30 days, consumables and plant material for the potato field experiment Xisen Potato Group: Three days staff cost for consultants of Chinese potato growing and market exploitation |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Assessing the reliability of RS data to predict crop disease (Small Project Award: SM001) |
| Organisation | Chinese Academy of Agricultural Sciences |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiangming Xu (NIAB EMR) Project Members: Dr Bo Li (NIAB EMR) and Dr Yilin Zhou (Chinese Academy of Agricultural Sciences) Project start date: 1 April 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof Zhou (CAAS) leads a national programme of developing decision-support tools for managing cereal diseases, including accurate assessment of diseases in a timely manner using RS tools. In the present project, he will provide published and unpublished data from his own research group in addition to obtaining further data in the spring of 2018. He will also discuss with other relevant researchers in China about the possibility of sourcing similar data in relation to crop physiology (particularly crop development in response to drought) and other diseases. |
| Impact | Liu et al. (2018) Detecting wheat powdery mildew and predicting grain yield using unmanned aerial photography. Plant Dis. 2018 Oct;102(10):1981-1988. Prof Xiangming XU visited IPP-CAAS (Beijing) and NWSUAF (Northwest A&F University, Yangling, China) to discuss RS of cereal diseases with Prof Zhou of IPP-CAAS, and Prof Hu of NWSUAF. Prof Xiangming Xu is to visit Prof Zhou to discuss experimental work in 2019. Prof Xu met Prof Chen of IPP-CAAS, project lead of wheat rust management in China, and discussed possible collaborative research on rust epidemiology and management. |
| Start Year | 2018 |
| Description | Assessing the reliability of RS data to predict crop disease (Small Project Award: SM001) |
| Organisation | National Institute of Agronomy and Botany (NIAB) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiangming Xu (NIAB EMR) Project Members: Dr Bo Li (NIAB EMR) and Dr Yilin Zhou (Chinese Academy of Agricultural Sciences) Project start date: 1 April 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof Zhou (CAAS) leads a national programme of developing decision-support tools for managing cereal diseases, including accurate assessment of diseases in a timely manner using RS tools. In the present project, he will provide published and unpublished data from his own research group in addition to obtaining further data in the spring of 2018. He will also discuss with other relevant researchers in China about the possibility of sourcing similar data in relation to crop physiology (particularly crop development in response to drought) and other diseases. |
| Impact | Liu et al. (2018) Detecting wheat powdery mildew and predicting grain yield using unmanned aerial photography. Plant Dis. 2018 Oct;102(10):1981-1988. Prof Xiangming XU visited IPP-CAAS (Beijing) and NWSUAF (Northwest A&F University, Yangling, China) to discuss RS of cereal diseases with Prof Zhou of IPP-CAAS, and Prof Hu of NWSUAF. Prof Xiangming Xu is to visit Prof Zhou to discuss experimental work in 2019. Prof Xu met Prof Chen of IPP-CAAS, project lead of wheat rust management in China, and discussed possible collaborative research on rust epidemiology and management. |
| Start Year | 2018 |
| Description | Automated image analysis and processing using UAV-deployed remote sensors (Small Project Award: SM003) |
| Organisation | Earlham Institute |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Ji Zhou (Earlham Institute) Project Members: Prof Tao Cheng (Nanjing Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: Development of an automated image analysis solution to identify key wheat growth stages based on large aerial images. |
| Collaborator Contribution | In-kind contribution from Nanjing Agricultural University (NAU), including NAU's field trial UAV/light aircraft images, NAU PI's time commitment (5% for the duration of the project). NAU PI's graduate students will be involved in collecting extra aerial imagery data, testing and verifying analysis results. |
| Impact | Information pending |
| Start Year | 2018 |
| Description | Automated image analysis and processing using UAV-deployed remote sensors (Small Project Award: SM003) |
| Organisation | Nanjing Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Ji Zhou (Earlham Institute) Project Members: Prof Tao Cheng (Nanjing Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: Development of an automated image analysis solution to identify key wheat growth stages based on large aerial images. |
| Collaborator Contribution | In-kind contribution from Nanjing Agricultural University (NAU), including NAU's field trial UAV/light aircraft images, NAU PI's time commitment (5% for the duration of the project). NAU PI's graduate students will be involved in collecting extra aerial imagery data, testing and verifying analysis results. |
| Impact | Information pending |
| Start Year | 2018 |
| Description | Autonomous vehicle delivery of more precise pesticide application (Small Project Award: SM013) |
| Organisation | Jiangsu University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Sujit Baliyarasimhuni and Prof Wen-Hua Chen (Loughborough University) Project Members: Dr Yue Shen (Jiangsu University), Mr Yiming Cui (Guangyi Mechanical and Electrical Machines Ltd) Project start date: 1 Jan 2018 Duration: Four months Project Summary: Autonomous safe driving system for agriculture spray machines. |
| Collaborator Contribution | Jiangsu University will allow Prof. Shen to spend 10% of his time on this project, provide access to the farming machine, human resources who are trained professionals for system integration and operating the machine (2 people for 4 months), host a researcher from the UK during the system integration phase, utilize associated grants between UK-China for this project, and provide the hardware and software interface for their farming machine. Loughborough University will utilize some associated grants for additional expenses and student time involving testing and system integration, facilitate its Husky robot for testing and system integration, provide its laboratory facilities along with licenced software, and provide two MSc Engineering students to work on the project for 4 months. |
| Impact | Developed: (i) a high accurate location estimates using particle filter, which both considers vehicle dynamics and RTK-GPS measurements. The errors are in the range of centimetres which will be highly desirable for precision agriculture application; (ii) a novel navigation algorithm is developed which gives high precision navigation by fusing information of crop line and outputs from particle filter; (iii) two kinds of collision avoidance algorithms including LIDAR based approach and computer vison-based approach are implemented in a test bed and validated in real world scenarios. Discussions with John Deere and other agriculture robotics companies at IROS conference in Madrid regarding future collaborations. |
| Start Year | 2018 |
| Description | Autonomous vehicle delivery of more precise pesticide application (Small Project Award: SM013) |
| Organisation | Loughborough University |
| Department | Department of Aeronautical and Automotive Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Sujit Baliyarasimhuni and Prof Wen-Hua Chen (Loughborough University) Project Members: Dr Yue Shen (Jiangsu University), Mr Yiming Cui (Guangyi Mechanical and Electrical Machines Ltd) Project start date: 1 Jan 2018 Duration: Four months Project Summary: Autonomous safe driving system for agriculture spray machines. |
| Collaborator Contribution | Jiangsu University will allow Prof. Shen to spend 10% of his time on this project, provide access to the farming machine, human resources who are trained professionals for system integration and operating the machine (2 people for 4 months), host a researcher from the UK during the system integration phase, utilize associated grants between UK-China for this project, and provide the hardware and software interface for their farming machine. Loughborough University will utilize some associated grants for additional expenses and student time involving testing and system integration, facilitate its Husky robot for testing and system integration, provide its laboratory facilities along with licenced software, and provide two MSc Engineering students to work on the project for 4 months. |
| Impact | Developed: (i) a high accurate location estimates using particle filter, which both considers vehicle dynamics and RTK-GPS measurements. The errors are in the range of centimetres which will be highly desirable for precision agriculture application; (ii) a novel navigation algorithm is developed which gives high precision navigation by fusing information of crop line and outputs from particle filter; (iii) two kinds of collision avoidance algorithms including LIDAR based approach and computer vison-based approach are implemented in a test bed and validated in real world scenarios. Discussions with John Deere and other agriculture robotics companies at IROS conference in Madrid regarding future collaborations. |
| Start Year | 2018 |
| Description | Autonomous vehicle or UAV-mounted sensing systems (Small Project Award: SM009) |
| Organisation | Henan University of Science and Technology |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Bruce Grieve (University of Manchester) Project Members: Prof Jiangtao Ji (Henan University of Science and Technology) Project start date: 1 March 2018 Duration: 12 months Project Summary: Exploration of opportunities to co-develop novel semi-autonomous approaches for rural communities in China |
| Collaborator Contribution | The University of Manchester will exploit prior research in multispectral imaging systems under the Innovate-UK and EPSRC supported projects in this area as well as utilise the outputs from two ongoing automation projects for in-field vegetables management on tractor and UAV (tethered balloon) based field monitoring systems, to form key elements of the proposed report from the project. Further partnering with members of the N8 Agri-Food programme will be brokered within the project as well as with the GCF IKnowFood project. The China partners have undertaken national, provincial and ministerial level scientific research projects, and one major project of intelligent agricultural machinery is funded by the MoST. Total amount of the funds is more than 4 million yuan. The group has rich experience in the research and development of agricultural machinery parts and components. The sensors needed for field information acquisition must be integrated into the power machinery and vehicles that are compatible with their functions. Special mechanisms are needed to implement variable spraying of herbicides. The China partners' rich experience in the development of agricultural machinery parts and components has laid a solid foundation for the research and development of key technology and equipment for the intelligent management of vegetable producing in the field. 1. Method of detecting the moving characteristics of transplanting robot and grasping seedling, 2.Control of the seeding quality based on integration and feedback of multiple information, 3. Removal vibration energy and vibration balancing of the high speed transplanting equipment, 4. Research and development of harvest technology equipment for vegetable seed breeding. Total: 5.23 Million RMB |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Autonomous vehicle or UAV-mounted sensing systems (Small Project Award: SM009) |
| Organisation | University of Manchester |
| Department | School of Electrical and Electronic Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Bruce Grieve (University of Manchester) Project Members: Prof Jiangtao Ji (Henan University of Science and Technology) Project start date: 1 March 2018 Duration: 12 months Project Summary: Exploration of opportunities to co-develop novel semi-autonomous approaches for rural communities in China |
| Collaborator Contribution | The University of Manchester will exploit prior research in multispectral imaging systems under the Innovate-UK and EPSRC supported projects in this area as well as utilise the outputs from two ongoing automation projects for in-field vegetables management on tractor and UAV (tethered balloon) based field monitoring systems, to form key elements of the proposed report from the project. Further partnering with members of the N8 Agri-Food programme will be brokered within the project as well as with the GCF IKnowFood project. The China partners have undertaken national, provincial and ministerial level scientific research projects, and one major project of intelligent agricultural machinery is funded by the MoST. Total amount of the funds is more than 4 million yuan. The group has rich experience in the research and development of agricultural machinery parts and components. The sensors needed for field information acquisition must be integrated into the power machinery and vehicles that are compatible with their functions. Special mechanisms are needed to implement variable spraying of herbicides. The China partners' rich experience in the development of agricultural machinery parts and components has laid a solid foundation for the research and development of key technology and equipment for the intelligent management of vegetable producing in the field. 1. Method of detecting the moving characteristics of transplanting robot and grasping seedling, 2.Control of the seeding quality based on integration and feedback of multiple information, 3. Removal vibration energy and vibration balancing of the high speed transplanting equipment, 4. Research and development of harvest technology equipment for vegetable seed breeding. Total: 5.23 Million RMB |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | China Robot Harvest ++ (Large Project Award: LG017) |
| Organisation | Fieldwork Robotics Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Dr. David Mozley (Fieldwork Robotics Ltd.), Mr. Xiaohui Mao, Wenhua Sun and Zhonglin Zhang, (Sunqiao), Pei Zhou (Shanghai Jiaotong University), Helen Geng (DeTao) Project start date: 1 April 2018 Duration: 10 months Project Summary: 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 which builds on a successful ATCNN Proof of Concept grant (PC014) where first selective harvesting of tomatoes with robots in China was demonstrated in Shanghai in summer 2017. We will work towards the exchange of robotics technology for the safe and efficient harvest of vegetable and fruit crops grown in the extensive glasshouses and plastic tunnels in the Shanghai District. |
| Collaborator Contribution | Sunqiao: Providing crop production resources for experimental work at Sunqiao Agricultural Park SJTU: Providing crop production resources for experimental work at Pujiang Green Valley Experimental Station DeTao: Travel and subsistence costs for visit from UK lead. |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | China Robot Harvest ++ (Large Project Award: LG017) |
| Organisation | Shanghai Jiao Tong University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Dr. David Mozley (Fieldwork Robotics Ltd.), Mr. Xiaohui Mao, Wenhua Sun and Zhonglin Zhang, (Sunqiao), Pei Zhou (Shanghai Jiaotong University), Helen Geng (DeTao) Project start date: 1 April 2018 Duration: 10 months Project Summary: 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 which builds on a successful ATCNN Proof of Concept grant (PC014) where first selective harvesting of tomatoes with robots in China was demonstrated in Shanghai in summer 2017. We will work towards the exchange of robotics technology for the safe and efficient harvest of vegetable and fruit crops grown in the extensive glasshouses and plastic tunnels in the Shanghai District. |
| Collaborator Contribution | Sunqiao: Providing crop production resources for experimental work at Sunqiao Agricultural Park SJTU: Providing crop production resources for experimental work at Pujiang Green Valley Experimental Station DeTao: Travel and subsistence costs for visit from UK lead. |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | China Robot Harvest ++ (Large Project Award: LG017) |
| Organisation | University of Plymouth |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Martin Stoelen and Prof Mick Fuller (University of Plymouth) Project Members: Dr. David Mozley (Fieldwork Robotics Ltd.), Mr. Xiaohui Mao, Wenhua Sun and Zhonglin Zhang, (Sunqiao), Pei Zhou (Shanghai Jiaotong University), Helen Geng (DeTao) Project start date: 1 April 2018 Duration: 10 months Project Summary: 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 which builds on a successful ATCNN Proof of Concept grant (PC014) where first selective harvesting of tomatoes with robots in China was demonstrated in Shanghai in summer 2017. We will work towards the exchange of robotics technology for the safe and efficient harvest of vegetable and fruit crops grown in the extensive glasshouses and plastic tunnels in the Shanghai District. |
| Collaborator Contribution | Sunqiao: Providing crop production resources for experimental work at Sunqiao Agricultural Park SJTU: Providing crop production resources for experimental work at Pujiang Green Valley Experimental Station DeTao: Travel and subsistence costs for visit from UK lead. |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Data innovations and sustainability in agri-food supply chains: Evidence from Henan Province, China (Pathfinder Award: PF006) |
| Organisation | Henan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Wantao Yu (University of Kent) Project Members: Prof. Ramakrishnan Ramanathan and Prof. Yanqing Duan (University of Bedfordshire); Dr Jiehui Yang (Henan University) Project start date: 1 August 2017 Duration: One month Project Summary: UK experts in the field of big data and agriculture sustainability and representatives from the Chinese agri-food sector and academics came together at a workshop to assess current practices in China on data innovations in the agri-food industry, learn from best practice examples from the UK and to identify opportunities for further collaboration between Chinese and UK partners. |
| Collaborator Contribution | Henan University will bear staff costs of its staff member (Dr Jiehui Yang), and provide partial funding to support the running and organisation of the workshop in China. Henan University will pay workshop participants for travelling expenses in China including the accommodation and the food. The University will also pay for the workshop costs, including the venue, the food, the honoraria for invited speakers, etc. In addition, Henan University will offer help and resources to disseminate the outcomes of the workshop to the community using a variety of social media tools. UK universities will bear a part of staff costs from their respective organisations. |
| Impact | The workshop has been successful in achieving its stated objectives of bringing together UK experts in the field of big data and agriculture sustainability with representatives in Chinese agri-food sector and other academics, and assessing current practice in China on data innovations in the agri-food industry. Collaboration opportunities were identified. |
| Start Year | 2017 |
| Description | Data innovations and sustainability in agri-food supply chains: Evidence from Henan Province, China (Pathfinder Award: PF006) |
| Organisation | University of Bedfordshire |
| Department | Business School |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Wantao Yu (University of Kent) Project Members: Prof. Ramakrishnan Ramanathan and Prof. Yanqing Duan (University of Bedfordshire); Dr Jiehui Yang (Henan University) Project start date: 1 August 2017 Duration: One month Project Summary: UK experts in the field of big data and agriculture sustainability and representatives from the Chinese agri-food sector and academics came together at a workshop to assess current practices in China on data innovations in the agri-food industry, learn from best practice examples from the UK and to identify opportunities for further collaboration between Chinese and UK partners. |
| Collaborator Contribution | Henan University will bear staff costs of its staff member (Dr Jiehui Yang), and provide partial funding to support the running and organisation of the workshop in China. Henan University will pay workshop participants for travelling expenses in China including the accommodation and the food. The University will also pay for the workshop costs, including the venue, the food, the honoraria for invited speakers, etc. In addition, Henan University will offer help and resources to disseminate the outcomes of the workshop to the community using a variety of social media tools. UK universities will bear a part of staff costs from their respective organisations. |
| Impact | The workshop has been successful in achieving its stated objectives of bringing together UK experts in the field of big data and agriculture sustainability with representatives in Chinese agri-food sector and other academics, and assessing current practice in China on data innovations in the agri-food industry. Collaboration opportunities were identified. |
| Start Year | 2017 |
| Description | Data innovations and sustainability in agri-food supply chains: Evidence from Henan Province, China (Pathfinder Award: PF006) |
| Organisation | University of Kent |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Wantao Yu (University of Kent) Project Members: Prof. Ramakrishnan Ramanathan and Prof. Yanqing Duan (University of Bedfordshire); Dr Jiehui Yang (Henan University) Project start date: 1 August 2017 Duration: One month Project Summary: UK experts in the field of big data and agriculture sustainability and representatives from the Chinese agri-food sector and academics came together at a workshop to assess current practices in China on data innovations in the agri-food industry, learn from best practice examples from the UK and to identify opportunities for further collaboration between Chinese and UK partners. |
| Collaborator Contribution | Henan University will bear staff costs of its staff member (Dr Jiehui Yang), and provide partial funding to support the running and organisation of the workshop in China. Henan University will pay workshop participants for travelling expenses in China including the accommodation and the food. The University will also pay for the workshop costs, including the venue, the food, the honoraria for invited speakers, etc. In addition, Henan University will offer help and resources to disseminate the outcomes of the workshop to the community using a variety of social media tools. UK universities will bear a part of staff costs from their respective organisations. |
| Impact | The workshop has been successful in achieving its stated objectives of bringing together UK experts in the field of big data and agriculture sustainability with representatives in Chinese agri-food sector and other academics, and assessing current practice in China on data innovations in the agri-food industry. Collaboration opportunities were identified. |
| Start Year | 2017 |
| Description | Diagnosis, data assimilation and decision-making systems for precision management of water and nitrogen in the Southern China (Large Project Award: LG007) |
| Organisation | Academy of Sciences of the Czech Republic |
| Department | Global Change Research Institute |
| Country | Czech Republic |
| Sector | Charity/Non Profit |
| PI Contribution | Project Lead(s): Prof. Mathew Williams (University of Edinburgh) Project Members: Prof. Liangsheng Shi (Wuhan University), Dr Kai Huang (Guangxi Institute of Hydraulic Research), Guangxi JJR Science and Technology Co Ltd. Project start date: 1 April 2018 Duration: 10 months Project Summary: To work with Chinese partners, farmers and end users in the application and deployment of novel crop sensing, diagnostic technologies, and decision support system for irrigation and fertilization and to develop a tool that can predict and diagnose crop response to water and nutrient related limits. |
| Collaborator Contribution | Wuhan University: Facility service and maintenance provided zero cost, access to experimental facilities, equipment and data, staff support for data assimilation programming. Guangxi Institute of Hydraulic Research: Technical support at zero cost (400 hours), access to experimental fields and data Guangxi JJR Science and Technology Co Ltd: Links to farmers and industry in target regions |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Diagnosis, data assimilation and decision-making systems for precision management of water and nitrogen in the Southern China (Large Project Award: LG007) |
| Organisation | Wuhan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof. Mathew Williams (University of Edinburgh) Project Members: Prof. Liangsheng Shi (Wuhan University), Dr Kai Huang (Guangxi Institute of Hydraulic Research), Guangxi JJR Science and Technology Co Ltd. Project start date: 1 April 2018 Duration: 10 months Project Summary: To work with Chinese partners, farmers and end users in the application and deployment of novel crop sensing, diagnostic technologies, and decision support system for irrigation and fertilization and to develop a tool that can predict and diagnose crop response to water and nutrient related limits. |
| Collaborator Contribution | Wuhan University: Facility service and maintenance provided zero cost, access to experimental facilities, equipment and data, staff support for data assimilation programming. Guangxi Institute of Hydraulic Research: Technical support at zero cost (400 hours), access to experimental fields and data Guangxi JJR Science and Technology Co Ltd: Links to farmers and industry in target regions |
| Impact | Information pending completion of project. |
| Start Year | 2018 |
| Description | Feasibility Study of a Self-Propelled Capsule Robot for Irrigation Pipeline Inspection (Pathfinder Award: PF002) |
| Organisation | Shanghai Jiao Tong University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Yang LIU (University of Exeter). Project Members: Prof Zhike PENG (Shanghai Jiao Tong University); Dr. Haibo Jiang (Yancheng Teacher University); Dr. Yao Yan (University of Electronic Science and Technology of China); Dr. Chengcheng Wang (Shanghai Bioiris Co. Ltd) Project start date: 1 July 2017 Duration: One month Project Summary: This project aimed to carry out a feasibility study of using the self-propelled vibro-impact capsule robot for irrigation pipeline inspection in rural China. The project was led by Dr Yang Liu from the University of Exeter collaborating with a consortium of China's universities, including Shanghai Jiao Tong University, Yancheng Teacher University, the University of Electronic Science and Technology of China, and an end-user company, Shanghai Bioiris Co. Ltd. Investigations were carried out at the rural areas of Yancheng and Chengdu in Jiangsu and Sichuan province, respectively. The purpose of using the novel capsule robot for irrigation pipelines is to inspect water loss due to pipeline damage/aging and monitor water quality, in order to address the water scarcity and food security issues in China. |
| Collaborator Contribution | Shanghai Jiao Tong University: Professor Zhike Peng will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the proposed project. One PhD student (50% FTE) and one post-doctoral research associate (50% FTE) from Professor Peng's research group will be involved in the next phase of the project to develop the proof-ofconcept prototype of the capsule robot. Shanghai Bioiris Co. Ltd: Dr. Chengcheng Wang will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the project. One mechanical and one electrical engineer will join in the meeting for feasibility study in Shanghai, and they will also be involved in the next phase of the project (at 50% FTE) to develop the proof-of-concept prototype of the capsule robot. Furthermore, Bioiris will provide the necessary hardware and equipment for developing the prototype. University of Electronic Science and Technology of China: Dr. Yao Yan will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Chengdu for the visiting team of Dr. Liu, Professor Peng, and Dr. Wang. Yancheng Teachers University: Dr. Haibo Jiang will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Yancheng for the visiting team. |
| Impact | Future work of this project will focus on the development of the capsule prototype, experimental testing, sensor integration, and field test. Future work will be dependent on the success of securing further funding from Agri-Tech in China Network+ Y. Yan, Y. Liu, and M. Liao, A comparative study of the vibro-impact capsule systems with one-sided and two-sided constraints, Nonlinear Dynamics, 89, 1063-1087, 2017 Y. Yan, Y. Liu, H. Jiang, and Z. Peng, Optimization and experimental verification of the vibro-impact capsule system in fluid pipeline, P I Mech Eng C-J Mec, 2019, Vol. 233(3) 880-894 Yan, Y., Liu, Y., Páez Chávez, J. et al. Meccanica (2018) 53: 1997. https://doi.org/10.1007/s11012-017-0801-3 |
| Start Year | 2017 |
| Description | Feasibility Study of a Self-Propelled Capsule Robot for Irrigation Pipeline Inspection (Pathfinder Award: PF002) |
| Organisation | University of Electronic Science and Technology of China (UESTC) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Yang LIU (University of Exeter). Project Members: Prof Zhike PENG (Shanghai Jiao Tong University); Dr. Haibo Jiang (Yancheng Teacher University); Dr. Yao Yan (University of Electronic Science and Technology of China); Dr. Chengcheng Wang (Shanghai Bioiris Co. Ltd) Project start date: 1 July 2017 Duration: One month Project Summary: This project aimed to carry out a feasibility study of using the self-propelled vibro-impact capsule robot for irrigation pipeline inspection in rural China. The project was led by Dr Yang Liu from the University of Exeter collaborating with a consortium of China's universities, including Shanghai Jiao Tong University, Yancheng Teacher University, the University of Electronic Science and Technology of China, and an end-user company, Shanghai Bioiris Co. Ltd. Investigations were carried out at the rural areas of Yancheng and Chengdu in Jiangsu and Sichuan province, respectively. The purpose of using the novel capsule robot for irrigation pipelines is to inspect water loss due to pipeline damage/aging and monitor water quality, in order to address the water scarcity and food security issues in China. |
| Collaborator Contribution | Shanghai Jiao Tong University: Professor Zhike Peng will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the proposed project. One PhD student (50% FTE) and one post-doctoral research associate (50% FTE) from Professor Peng's research group will be involved in the next phase of the project to develop the proof-ofconcept prototype of the capsule robot. Shanghai Bioiris Co. Ltd: Dr. Chengcheng Wang will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the project. One mechanical and one electrical engineer will join in the meeting for feasibility study in Shanghai, and they will also be involved in the next phase of the project (at 50% FTE) to develop the proof-of-concept prototype of the capsule robot. Furthermore, Bioiris will provide the necessary hardware and equipment for developing the prototype. University of Electronic Science and Technology of China: Dr. Yao Yan will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Chengdu for the visiting team of Dr. Liu, Professor Peng, and Dr. Wang. Yancheng Teachers University: Dr. Haibo Jiang will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Yancheng for the visiting team. |
| Impact | Future work of this project will focus on the development of the capsule prototype, experimental testing, sensor integration, and field test. Future work will be dependent on the success of securing further funding from Agri-Tech in China Network+ Y. Yan, Y. Liu, and M. Liao, A comparative study of the vibro-impact capsule systems with one-sided and two-sided constraints, Nonlinear Dynamics, 89, 1063-1087, 2017 Y. Yan, Y. Liu, H. Jiang, and Z. Peng, Optimization and experimental verification of the vibro-impact capsule system in fluid pipeline, P I Mech Eng C-J Mec, 2019, Vol. 233(3) 880-894 Yan, Y., Liu, Y., Páez Chávez, J. et al. Meccanica (2018) 53: 1997. https://doi.org/10.1007/s11012-017-0801-3 |
| Start Year | 2017 |
| Description | Feasibility Study of a Self-Propelled Capsule Robot for Irrigation Pipeline Inspection (Pathfinder Award: PF002) |
| Organisation | University of Exeter |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Yang LIU (University of Exeter). Project Members: Prof Zhike PENG (Shanghai Jiao Tong University); Dr. Haibo Jiang (Yancheng Teacher University); Dr. Yao Yan (University of Electronic Science and Technology of China); Dr. Chengcheng Wang (Shanghai Bioiris Co. Ltd) Project start date: 1 July 2017 Duration: One month Project Summary: This project aimed to carry out a feasibility study of using the self-propelled vibro-impact capsule robot for irrigation pipeline inspection in rural China. The project was led by Dr Yang Liu from the University of Exeter collaborating with a consortium of China's universities, including Shanghai Jiao Tong University, Yancheng Teacher University, the University of Electronic Science and Technology of China, and an end-user company, Shanghai Bioiris Co. Ltd. Investigations were carried out at the rural areas of Yancheng and Chengdu in Jiangsu and Sichuan province, respectively. The purpose of using the novel capsule robot for irrigation pipelines is to inspect water loss due to pipeline damage/aging and monitor water quality, in order to address the water scarcity and food security issues in China. |
| Collaborator Contribution | Shanghai Jiao Tong University: Professor Zhike Peng will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the proposed project. One PhD student (50% FTE) and one post-doctoral research associate (50% FTE) from Professor Peng's research group will be involved in the next phase of the project to develop the proof-ofconcept prototype of the capsule robot. Shanghai Bioiris Co. Ltd: Dr. Chengcheng Wang will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the project. One mechanical and one electrical engineer will join in the meeting for feasibility study in Shanghai, and they will also be involved in the next phase of the project (at 50% FTE) to develop the proof-of-concept prototype of the capsule robot. Furthermore, Bioiris will provide the necessary hardware and equipment for developing the prototype. University of Electronic Science and Technology of China: Dr. Yao Yan will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Chengdu for the visiting team of Dr. Liu, Professor Peng, and Dr. Wang. Yancheng Teachers University: Dr. Haibo Jiang will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Yancheng for the visiting team. |
| Impact | Future work of this project will focus on the development of the capsule prototype, experimental testing, sensor integration, and field test. Future work will be dependent on the success of securing further funding from Agri-Tech in China Network+ Y. Yan, Y. Liu, and M. Liao, A comparative study of the vibro-impact capsule systems with one-sided and two-sided constraints, Nonlinear Dynamics, 89, 1063-1087, 2017 Y. Yan, Y. Liu, H. Jiang, and Z. Peng, Optimization and experimental verification of the vibro-impact capsule system in fluid pipeline, P I Mech Eng C-J Mec, 2019, Vol. 233(3) 880-894 Yan, Y., Liu, Y., Páez Chávez, J. et al. Meccanica (2018) 53: 1997. https://doi.org/10.1007/s11012-017-0801-3 |
| Start Year | 2017 |
| Description | Feasibility Study of a Self-Propelled Capsule Robot for Irrigation Pipeline Inspection (Pathfinder Award: PF002) |
| Organisation | Yancheng Teachers University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Yang LIU (University of Exeter). Project Members: Prof Zhike PENG (Shanghai Jiao Tong University); Dr. Haibo Jiang (Yancheng Teacher University); Dr. Yao Yan (University of Electronic Science and Technology of China); Dr. Chengcheng Wang (Shanghai Bioiris Co. Ltd) Project start date: 1 July 2017 Duration: One month Project Summary: This project aimed to carry out a feasibility study of using the self-propelled vibro-impact capsule robot for irrigation pipeline inspection in rural China. The project was led by Dr Yang Liu from the University of Exeter collaborating with a consortium of China's universities, including Shanghai Jiao Tong University, Yancheng Teacher University, the University of Electronic Science and Technology of China, and an end-user company, Shanghai Bioiris Co. Ltd. Investigations were carried out at the rural areas of Yancheng and Chengdu in Jiangsu and Sichuan province, respectively. The purpose of using the novel capsule robot for irrigation pipelines is to inspect water loss due to pipeline damage/aging and monitor water quality, in order to address the water scarcity and food security issues in China. |
| Collaborator Contribution | Shanghai Jiao Tong University: Professor Zhike Peng will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the proposed project. One PhD student (50% FTE) and one post-doctoral research associate (50% FTE) from Professor Peng's research group will be involved in the next phase of the project to develop the proof-ofconcept prototype of the capsule robot. Shanghai Bioiris Co. Ltd: Dr. Chengcheng Wang will contribute 100% of his time to carry out feasibility study with Dr. Liu in Chengdu and Yancheng for the entire duration of the project. One mechanical and one electrical engineer will join in the meeting for feasibility study in Shanghai, and they will also be involved in the next phase of the project (at 50% FTE) to develop the proof-of-concept prototype of the capsule robot. Furthermore, Bioiris will provide the necessary hardware and equipment for developing the prototype. University of Electronic Science and Technology of China: Dr. Yao Yan will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Chengdu for the visiting team of Dr. Liu, Professor Peng, and Dr. Wang. Yancheng Teachers University: Dr. Haibo Jiang will make financial contributions to the proposed project by covering the domestic flight tickets, accommodation, and subsistence in Yancheng for the visiting team. |
| Impact | Future work of this project will focus on the development of the capsule prototype, experimental testing, sensor integration, and field test. Future work will be dependent on the success of securing further funding from Agri-Tech in China Network+ Y. Yan, Y. Liu, and M. Liao, A comparative study of the vibro-impact capsule systems with one-sided and two-sided constraints, Nonlinear Dynamics, 89, 1063-1087, 2017 Y. Yan, Y. Liu, H. Jiang, and Z. Peng, Optimization and experimental verification of the vibro-impact capsule system in fluid pipeline, P I Mech Eng C-J Mec, 2019, Vol. 233(3) 880-894 Yan, Y., Liu, Y., Páez Chávez, J. et al. Meccanica (2018) 53: 1997. https://doi.org/10.1007/s11012-017-0801-3 |
| Start Year | 2017 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | Bangor University |
| Department | School of Environment, Natural Resources and Geography |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | Chinese Academy of Sciences |
| Country | China |
| Sector | Public |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | RSK ADAS Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | Rothamsted Research |
| Department | Sustainable Agriculture Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | GIS systems to support in-field manure systems (Small Project Award: SM019) |
| Organisation | University of East Anglia |
| Department | School of International Development UEA |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Mr John Williams (RSK ADAS Ltd) Project Members: Prof. Dave Chadwick (Bangor University), Prof. Tom Misselbrook (Rothamsted Research), Dr. Yuelai Lu (University of East Anglia), Dr. Ma Lin (Chinese Academy of Sciences) Prof. Fusuo Zhang (China Agricultural University) Project start date: 1 March 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | John Williams, Dave Chadwick and Tom Misselbrook are part of the UK-China Virtual Joint Centres for Improving NUE (N-Circle and CINAg). Flights will be paid for from the projects. Yuelai Lu brings his knowledge and experience of Chinese Agricultural Policy and Industry to the project, and will ensure that project information is communicated with UK and Chinese researchers, Industry and Policy groups via the SAIN website and Newsletters and UK China Knowledge Sharing and Mutual Learning Platform. Dr Ma Lin and Prof Fusuo Zhang are also part of the CINAG project and will host the inception workshop in China. They also provide direct communication with intensive livestock producers, policy makers, regional governments and farming households via the SBT Programme, which will eventually benefit from this guidance on organic manure management. Our Chinese partners are also ideally placed to help source the data needed to underpin the framework. |
| Impact | Following this workshop, the Rural Energy and Environment Agency (REEA) of MARA, China Agricultural University and SAIN are planning a joint event to bring together the interested UK and Chinese partners (governmental agencies, public organisations, business, academics) to further investigate collaboration opportunities and to develop cooperation proposals for projects to fill the evidence gaps identified in this study. This further event is likely to be held in March 2019 to connect to the REEA's national eco-agricultural conference. |
| Start Year | 2018 |
| Description | Highly Efficient Intelligent Irrigation Systems (Proof-of-Concept Award: PC003) |
| Organisation | Jiangsu University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Wen-Hua Chen (Loughborough University) Project Members: Prof Weidong Shi (Jiangsu University) Project start date: 1 April 2017 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Chinese partner Jiangsu University will provide data of their water saving irrigation systems, the test facilities, and the manpower involved in this project as required including the feasibility of the concept, the architecture of the system, the needs analysis and assessment, the implementation study and the joint effort in co-developing a proposal for further funding. They will also provide accommodation and other associated costs during the UK team's visit to Jiangsu University. To facilitate progress, it is committed that two researchers from Jiangsu University will visit Loughborough for further discussion of collaboration using their own financial resources. They also have a significant of number of ongoing projects in water saving irrigation systems. Storing and processing images and data from satellites requires significant computing power and IT support. Loughborough University will provides IT support for this project and, if necessary, give the team accessing to high performance computing facilities it hosts. |
| Impact | The idea of this proposal is to develop highly efficient intelligent irrigation systems based on the optimized irrigation decision made by accommodating various sources of data and information along with its implementation using water saving irrigation machines. The research results validate the feasibility of the idea. |
| Start Year | 2017 |
| Description | Highly Efficient Intelligent Irrigation Systems (Proof-of-Concept Award: PC003) |
| Organisation | Loughborough University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Wen-Hua Chen (Loughborough University) Project Members: Prof Weidong Shi (Jiangsu University) Project start date: 1 April 2017 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Chinese partner Jiangsu University will provide data of their water saving irrigation systems, the test facilities, and the manpower involved in this project as required including the feasibility of the concept, the architecture of the system, the needs analysis and assessment, the implementation study and the joint effort in co-developing a proposal for further funding. They will also provide accommodation and other associated costs during the UK team's visit to Jiangsu University. To facilitate progress, it is committed that two researchers from Jiangsu University will visit Loughborough for further discussion of collaboration using their own financial resources. They also have a significant of number of ongoing projects in water saving irrigation systems. Storing and processing images and data from satellites requires significant computing power and IT support. Loughborough University will provides IT support for this project and, if necessary, give the team accessing to high performance computing facilities it hosts. |
| Impact | The idea of this proposal is to develop highly efficient intelligent irrigation systems based on the optimized irrigation decision made by accommodating various sources of data and information along with its implementation using water saving irrigation machines. The research results validate the feasibility of the idea. |
| Start Year | 2017 |
| Description | Improving satellite-based models using new satellite data (Small Project Award: SM008) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Kevin Tansey (University of Leicester) Project Members: Dr James Wheeler (University of Leicester), Prof Pengxin Wang (China Lead - China Agriculture University), Dr Li Li, Mr Xijia Zhou, Ms Qingling Kong, Ms Xuan Qi, Ms Lianxiang Xu Project start date: 1 Feb 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof. Tansey is a member of the Leicester Institute for Space and Earth Observation. He will also make the National Centre for Earth Observation (NCEO) programme aware of this activity, an organisation that is based at Leicester. Prof. Tansey will be supported to attend the workshop under the Chinese Government SAFE programme which he is involved with. He is required to spend up to 30 days in China each year for the next 3 years. This is an in-kind contribution of approximately £5000/year by the Chinese. Dr. Li of CAU is currently researching the use of S-1 data to yield information about crop type, structure and growth and will develop her work into soil moisture retrievals alongside this project. Prof Wang of CAU has developed the drought model and wheat yield model and will support, with the help of PhD/MSc students, to consider the necessary changes to the model to enable it to work with Sentinel data |
| Impact | Science questions to develop in the future: 1. Can we obtain results that are more accurate from Sentinel data as opposed to reliance on MODIS products. This question is still to be fully answered 2. What might the results regarding drought indices mean to planners and farmers? 3. Develop a framework to monitor crop growth condition and estimate crop yields using Sentinel data 4. Develop a requirement and a need to process and use of Sentinel-2 data. Data transfer/exchanges: 1. Setup a long-term exchange of Sentinel-1 and Sentinel-3 satellite extractions over China and in situ data from Chinese field sites 2.. Objective to keep the exchange of data going for at least a year or more in order to investigate the seasonal and monthly differences, which are very important for crop monitoring 3. Utilise satellite data from the series of Chinese Gaofen (GF) satellites if appropriate |
| Start Year | 2018 |
| Description | Improving satellite-based models using new satellite data (Small Project Award: SM008) |
| Organisation | Keele University |
| Department | School of Geography, Geology and the Environment |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Kevin Tansey (University of Leicester) Project Members: Dr James Wheeler (University of Leicester), Prof Pengxin Wang (China Lead - China Agriculture University), Dr Li Li, Mr Xijia Zhou, Ms Qingling Kong, Ms Xuan Qi, Ms Lianxiang Xu Project start date: 1 Feb 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof. Tansey is a member of the Leicester Institute for Space and Earth Observation. He will also make the National Centre for Earth Observation (NCEO) programme aware of this activity, an organisation that is based at Leicester. Prof. Tansey will be supported to attend the workshop under the Chinese Government SAFE programme which he is involved with. He is required to spend up to 30 days in China each year for the next 3 years. This is an in-kind contribution of approximately £5000/year by the Chinese. Dr. Li of CAU is currently researching the use of S-1 data to yield information about crop type, structure and growth and will develop her work into soil moisture retrievals alongside this project. Prof Wang of CAU has developed the drought model and wheat yield model and will support, with the help of PhD/MSc students, to consider the necessary changes to the model to enable it to work with Sentinel data |
| Impact | Science questions to develop in the future: 1. Can we obtain results that are more accurate from Sentinel data as opposed to reliance on MODIS products. This question is still to be fully answered 2. What might the results regarding drought indices mean to planners and farmers? 3. Develop a framework to monitor crop growth condition and estimate crop yields using Sentinel data 4. Develop a requirement and a need to process and use of Sentinel-2 data. Data transfer/exchanges: 1. Setup a long-term exchange of Sentinel-1 and Sentinel-3 satellite extractions over China and in situ data from Chinese field sites 2.. Objective to keep the exchange of data going for at least a year or more in order to investigate the seasonal and monthly differences, which are very important for crop monitoring 3. Utilise satellite data from the series of Chinese Gaofen (GF) satellites if appropriate |
| Start Year | 2018 |
| Description | Informatics and network analysis of deep metagenomic sequences from the global soil metagenome project |
| Organisation | IBM |
| Department | IBM UK Labs Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Based on the preliminary analysis of the global soil metagenomes that are the subject of this collaboration, we recognised patterns that would benefit from deeper analyses. We approached IBM Research (UK) to discuss collaboration with the Computational Life Science programme and established a joint programme with the team led by Dr Ritesh Krishna. We provided the scientific questions, the biological knowledge and all of the data. |
| Collaborator Contribution | IBM have brought new analysis tools and high performance computer hardware to the project which means we can undertake analysis of the metagenomes in minutes compared with days and weeks on the Rothamsted cluster. They are also working with us on the development of new algorithms and on the interpretation of the results |
| Impact | This collaboration is highly multidisciplinary and brings together computer science, bioinformatics, mathematics, microbiology and genetics. the results include new tools for identifying differences in metagenomic sequences between treatments. The innovation is that the analysis is multi-scale and focused on functions that relate to critical soil properties including water storage, greenhouse gas emission and nutrient efficiency |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | Agricultural University of Hebei |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | Courtyard Agriculture Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | Henan Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | James Hutton Institute |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | RSK ADAS Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | Management zone delineation and decision support system for small scale farming at village level in North China Plain (Small Project Award: WK001) |
| Organisation | Rothamsted Research |
| Department | Sustainable Agriculture Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Davide Cammarano (James Hutton Institute) Project Members: Lucy Wilson (RSK ADAS Ltd); Dr Xiaoxian Zhang (Rothamsted Research); Zhigang Liu (Courtyard Agriculture Ltd); Prof Xuxin Miao (China Agricultural University); Prof Wenqi Ma (Agricultural University of Hebei); Prof Youliang Ye (Henan Agricultural University) Project start date: 1 April 2018 Duration: Six months Project Summary: A prototype Decision Support System, integrating the latest scientific advances, is going to be tested in Xushui village (Hebei). The end-users will be the advisors that will utilise the outputs to inform farmers on site-specific management. The system proposed will help quantifying the best amount of side-dressing nitrogen fertilization. The system has been conceptualised to work with minimum or no data because if we apply this system in other villages we should be able to do it without having to collect too many data. |
| Collaborator Contribution | The Chinese partners (CAU, Hebei and Hainan Agricultural Universities) will put several PhD and Master students who are currently working on the STB. They will also put their time and the currently Funded project that especially Prof Miao has on the STB sites. |
| Impact | Information pending submission of final project report. |
| Start Year | 2018 |
| Description | NeWMap: Enhanced farm-specific NutriEnt and Water stress Maps (Small Project Award: WK002) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jinghao Xue (University College London) Project Members: Prof Wen-Hua Chen (Loughborough University); Dr Zhichao Chen, Dr Weifeng Zhang, Dr Hongshuo Wang and Dr Wei Su (China Agricultural University) Project start date: 1 March 2018 Duration: 12 months Project Summary: This project aims to address the challenge that there is a need of field-specific advice for small-scale farming in China. About 70-80% of Chinese farmers have less than 0.5 ha, and it is very difficult and labour intensive to conduct field specific assessment in order to facilitate timely crop management, particularly fertiliser and water management. To mitigate this issue, we aim 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. |
| Collaborator Contribution | China Agricultural University: WP1 STB contribution of manpower and the ground - truth and UAV data collection. Research for WP2-4 (feature extraction; data fusion; nutrient and water stress mapping) |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | NeWMap: Enhanced farm-specific NutriEnt and Water stress Maps (Small Project Award: WK002) |
| Organisation | Loughborough University |
| Department | Department of Aeronautical and Automotive Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jinghao Xue (University College London) Project Members: Prof Wen-Hua Chen (Loughborough University); Dr Zhichao Chen, Dr Weifeng Zhang, Dr Hongshuo Wang and Dr Wei Su (China Agricultural University) Project start date: 1 March 2018 Duration: 12 months Project Summary: This project aims to address the challenge that there is a need of field-specific advice for small-scale farming in China. About 70-80% of Chinese farmers have less than 0.5 ha, and it is very difficult and labour intensive to conduct field specific assessment in order to facilitate timely crop management, particularly fertiliser and water management. To mitigate this issue, we aim 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. |
| Collaborator Contribution | China Agricultural University: WP1 STB contribution of manpower and the ground - truth and UAV data collection. Research for WP2-4 (feature extraction; data fusion; nutrient and water stress mapping) |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | NeWMap: Enhanced farm-specific NutriEnt and Water stress Maps (Small Project Award: WK002) |
| Organisation | University College London |
| Department | Department of Statistical Science |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jinghao Xue (University College London) Project Members: Prof Wen-Hua Chen (Loughborough University); Dr Zhichao Chen, Dr Weifeng Zhang, Dr Hongshuo Wang and Dr Wei Su (China Agricultural University) Project start date: 1 March 2018 Duration: 12 months Project Summary: This project aims to address the challenge that there is a need of field-specific advice for small-scale farming in China. About 70-80% of Chinese farmers have less than 0.5 ha, and it is very difficult and labour intensive to conduct field specific assessment in order to facilitate timely crop management, particularly fertiliser and water management. To mitigate this issue, we aim 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. |
| Collaborator Contribution | China Agricultural University: WP1 STB contribution of manpower and the ground - truth and UAV data collection. Research for WP2-4 (feature extraction; data fusion; nutrient and water stress mapping) |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Network+ Industry Partnerships |
| Organisation | AgSpace Agriculture Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | BASF |
| Country | Germany |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Carbon Trust |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Ecometrica Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Map of Agriculture Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Microsoft Research |
| Country | Global |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Syngenta International AG |
| Country | Switzerland |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ Industry Partnerships |
| Organisation | Velcourt Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We established this group of companies as an initial set of organisations interested in engaging in puli-private partnerships in China |
| Collaborator Contribution | These companies have taken part in workshops and some have established new projects in China e.g. AgSpace. |
| Impact | These partnership formed the initial core group of companies and through their networks we have now established network of more than 50 companies in China and the UK who are directly engaged in the Network+ |
| Start Year | 2016 |
| Description | Network+ academic partnerships |
| Organisation | Agrimetrics Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | I lead the research team and have enabled them to engage widely in China with both potential academic and industry partners |
| Collaborator Contribution | We have formed a management group for the Network+ that has organised 3 international workshops, run two calls for funding, established an advisory group to review proposals and advise the Management Group, and funded 10 projects as public-private partnerships between the UK and China |
| Impact | This is a multidisciplinary partnership involving social scientists, physicists, agricultural and environmental scientists |
| Start Year | 2015 |
| Description | Network+ academic partnerships |
| Organisation | Scotland's Rural College |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | I lead the research team and have enabled them to engage widely in China with both potential academic and industry partners |
| Collaborator Contribution | We have formed a management group for the Network+ that has organised 3 international workshops, run two calls for funding, established an advisory group to review proposals and advise the Management Group, and funded 10 projects as public-private partnerships between the UK and China |
| Impact | This is a multidisciplinary partnership involving social scientists, physicists, agricultural and environmental scientists |
| Start Year | 2015 |
| Description | Network+ academic partnerships |
| Organisation | University of Edinburgh |
| Department | Medical School Edinburgh |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | I lead the research team and have enabled them to engage widely in China with both potential academic and industry partners |
| Collaborator Contribution | We have formed a management group for the Network+ that has organised 3 international workshops, run two calls for funding, established an advisory group to review proposals and advise the Management Group, and funded 10 projects as public-private partnerships between the UK and China |
| Impact | This is a multidisciplinary partnership involving social scientists, physicists, agricultural and environmental scientists |
| Start Year | 2015 |
| Description | Network+ academic partnerships |
| Organisation | University of Reading |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | I lead the research team and have enabled them to engage widely in China with both potential academic and industry partners |
| Collaborator Contribution | We have formed a management group for the Network+ that has organised 3 international workshops, run two calls for funding, established an advisory group to review proposals and advise the Management Group, and funded 10 projects as public-private partnerships between the UK and China |
| Impact | This is a multidisciplinary partnership involving social scientists, physicists, agricultural and environmental scientists |
| Start Year | 2015 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Agrimetrics Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Assimila Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Centre for Agriculture and Bioscience International |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Chinese Academy of Sciences |
| Country | China |
| Sector | Public |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Courtyard Agriculture Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Earlham Institute |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | GSMA |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Henan Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Henan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | IBM |
| Department | IBM UK Labs Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Manchester Metropolitan University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Manchester University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | National Institute of Agronomy and Botany (NIAB) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | RSK ADAS Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Roehampton University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | Rothamsted Research |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | University College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | University of Newcastle |
| Country | Australia |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Quzhou Agri-Tech Integration Programme |
| Organisation | University of Strathclyde |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Rather than fund more individual projects, this final phase of work (from summer 2018 to spring 2019) aims to: - bring together the developments that have been achieved so far - focus work at the China Agriculture University (CAU) experimental farm site at Quzhou, Hebei Province - create a prototype infrastructure to integrate the technologies and analytics already developed - enable the on-going development of the technologies and analytics explored in the Network+ beyond the end of the current programme (which ends in spring 2019) We recognise that not all technologies are ready for integration and that there will be knowledge gaps. For that reason, we propose the following objectives: - conduct a user requirements analysis with farmers and other stakeholders at Quzhou - review the data outputs of the existing projects along with other available technologies and prioritise sources of data generation for integration into the platform. - identify gaps in knowledge to integrate technologies at Quzhou - identify gaps in analytics required to enable inferences on the system of risks (e.g., pests and diseases, irrigation needs etc.) - design and build a prototype infrastructure, including an interface to support farmer decision making UK Lead: Prof John Crawford (Rothamsted Research); China Lead: Prof Weifeng Zhang (China Agricultural University). Work is focused into three workstreams dealing separately with Use Cases, Data and Technology Review, and Insights & Communication 1. Use cases. Tasks: (i) Identify potential use case studies based on farmer requirements analysis; (ii) Prioritise according to appropriate trade-off (according to need, and to data and technology availability) between supporting soil, nutrition, plant health, and irrigation management to provide prototype of a systems analysis tool; (iii) Develop appropriate interface protocols with data storage in collaboration with Stream 2; (iv) Develop proof-of-concept systems analysis tool based on chosen use-case(s). Leads: WP1 - Prof Xiu Yan (University of Strathclyde); WP2 - Dr Xiaoxian Zhang (Rothamsted Research); WP3 - Dr Nicola Pounder (Assimila Ltd); WP4 - Prof Liangxiu Han (Manchester Metropolitan University); WP5 - Dr Lily Zhang (NIAB EMR); WP6 - Dr Ji Zhou (Earlham Institute) 2. Data and technology review. Tasks: (i) Review project reports and work with project PI's to identify sources of data supported by N+ that are needed to meet the requirements of the farmers; (ii) Compile a report on additional commercially available technologies as sources of supplementary meta data, either to fill data gaps or to serve as a cross-validation of other data sources; (iii) Create and prioritise a shortlist of data sources to implement at Quzhou; (iv) Develop a set of protocols for necessary pre-processing, transformation, normalisation and consolidation; (v) Deploy relevant data sources at Quzhou. Leads: WP7 - Dr Bruce Grieve (Manchester University); WP8 - Dr Kenneth Tong (University College London); WP9 - Dr Allan Bartlett (GSMA); WP10 - Prof Wantao Yu (Roehampton University) 3. Insights and communication. Tasks: (i) Undertake a requirements analysis in collaboration with CAU and STB farmers; (ii) Review attributes of advice apps in non-ag settings to create a 'lessons learned' document; (iii) Review and assess existing apps; (iv) Build mock-up interface and hold user testing event with farmers and advisors in China; (v) Assess functionality gaps in existing apps and constraints in integration of functionalities; (vi) Synthesis and recommendations. Lead: WP11 - Lucy Wilson (RSK ADAS Ltd) |
| Collaborator Contribution | to follow |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Radar and Aerial Ecology Summer School (Intra-Project Partnership Award: IPP001) |
| Organisation | Chinese Academy of Agricultural Sciences |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jason Lim (Rothamsted Research) Project Members: Assoc. Prof. Jason Chapman (University of Exeter), Dr Xiongbing Tu (Chinese Academy of Agricultural Sciences), Prof Gao Hu (Nanjing Agricultural University) Project start date: 1 August 2017 Duration: 15 months Project Summary: 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). |
| Collaborator Contribution | Matched resources will come from CAAS and NAU: Staff time - helping to arrange radar import licence and deposit, assisting with teaching at the Summer School, and for some radar data analysis. Consumables - some costs incurred for moving the VLR, travel to and from Xilinhot, accommodation at Xilinhot. |
| Impact | Information pending submission of final project report. |
| Start Year | 2017 |
| Description | Radar and Aerial Ecology Summer School (Intra-Project Partnership Award: IPP001) |
| Organisation | Nanjing Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jason Lim (Rothamsted Research) Project Members: Assoc. Prof. Jason Chapman (University of Exeter), Dr Xiongbing Tu (Chinese Academy of Agricultural Sciences), Prof Gao Hu (Nanjing Agricultural University) Project start date: 1 August 2017 Duration: 15 months Project Summary: 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). |
| Collaborator Contribution | Matched resources will come from CAAS and NAU: Staff time - helping to arrange radar import licence and deposit, assisting with teaching at the Summer School, and for some radar data analysis. Consumables - some costs incurred for moving the VLR, travel to and from Xilinhot, accommodation at Xilinhot. |
| Impact | Information pending submission of final project report. |
| Start Year | 2017 |
| Description | Radar and Aerial Ecology Summer School (Intra-Project Partnership Award: IPP001) |
| Organisation | Rothamsted Research |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jason Lim (Rothamsted Research) Project Members: Assoc. Prof. Jason Chapman (University of Exeter), Dr Xiongbing Tu (Chinese Academy of Agricultural Sciences), Prof Gao Hu (Nanjing Agricultural University) Project start date: 1 August 2017 Duration: 15 months Project Summary: 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). |
| Collaborator Contribution | Matched resources will come from CAAS and NAU: Staff time - helping to arrange radar import licence and deposit, assisting with teaching at the Summer School, and for some radar data analysis. Consumables - some costs incurred for moving the VLR, travel to and from Xilinhot, accommodation at Xilinhot. |
| Impact | Information pending submission of final project report. |
| Start Year | 2017 |
| Description | Radar and Aerial Ecology Summer School (Intra-Project Partnership Award: IPP001) |
| Organisation | University of Exeter |
| Department | Environment and Sustainability Institute |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Jason Lim (Rothamsted Research) Project Members: Assoc. Prof. Jason Chapman (University of Exeter), Dr Xiongbing Tu (Chinese Academy of Agricultural Sciences), Prof Gao Hu (Nanjing Agricultural University) Project start date: 1 August 2017 Duration: 15 months Project Summary: 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). |
| Collaborator Contribution | Matched resources will come from CAAS and NAU: Staff time - helping to arrange radar import licence and deposit, assisting with teaching at the Summer School, and for some radar data analysis. Consumables - some costs incurred for moving the VLR, travel to and from Xilinhot, accommodation at Xilinhot. |
| Impact | Information pending submission of final project report. |
| Start Year | 2017 |
| Description | Scaling up from Village to County/Province Level to Support Science & Technology Backyard (STB) Programme for Innovation of Chinese Household-Based Small Farms (WK008) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Jinchang Ren, University of Strathclyde Project Members: Dr Vijay K Vohora (Mapping Earth Resources Ltd), Weifeng Zhang (China Agricultural University), Prof Zhongxin Chen (Institute of Agriculture Resources & Regional Planning, Chinese Academy of Agriculture Science ),Dr Xinying Xu (Taiyuan University of Technology) Project start date: 1 April 2018 Duration: 10 months Project Summary: Household-based small farms (HBSF) contribute to 96% of agriculture workers in China, 24% of the population. Suffering from low productivity, low efficiency and lack of knowledge/technology for sustainable development, especially in coping with limited resources and environmental issues, aging and poorly-educated HBSFs have become a critical problem in China. In recent years, the Science and Technology at Backyard (STB) programme was proposed to support HBSFs to gain technology inputs from universities and research institutes. Though successful in increasing the yield, the migration of STB from villages to higher county/province level is constrained, due mainly to the low-level automation and huge labours requested. Taking STBs in Laoling City and Yangxin County of Shandong Province as case studies, we aim to demonstrate feasible solutions for scaling up village-based STBs to upper level. By introducing remote sensing data and mapping to in-situ observations, associations are established to guide the operations at different stages to significantly reduce the labour cost for data acquisition for automatic estimation of population and yield. Also an audio-call based interface will be introduced in local dialects for more effective communication with HBSFs to fulfil the recommended operations. |
| Collaborator Contribution | UK Partners: Additional staff time, including academic staff, research staff and technical support; Software tools and platforms: The big data framework developed in UoS will be adapted to the project, with other software tools such as ENVI and Deep Learning machine (UoS) China Partners: In addition to the existing data recorded in the past, CAU will provide local knowledge, field survey and validation, where the staff time and access to the data will be critical to the success of the project; CAAS will provide fix-wing UAV and 2 trained technicians for data collection in the experiment region. Two research scientist and one PhD student will work for this project for 2 months. CAAS will also provide GF-1, GF-2 and possibly GF-6 satellite remote sensing data for the study area. The quantitative remote sensing inversion models of crop and land parameters including LAI, crop coverage, biomass, soil moisture from STFC-NSFC Newton fund project and other scientific research projects will be provided to this project for yield estimation. CAAS will also provide logistic supports for project meetings held in Beijing; TYUT will provide access to their sensors and staff time for design automated feedback device to communicate with HBSFs, these will include their staff time and facilities. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Scaling up from Village to County/Province Level to Support Science & Technology Backyard (STB) Programme for Innovation of Chinese Household-Based Small Farms (WK008) |
| Organisation | Chinese Academy of Agricultural Sciences |
| Department | Institute of Agriculture Resources & Regional Planning |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Jinchang Ren, University of Strathclyde Project Members: Dr Vijay K Vohora (Mapping Earth Resources Ltd), Weifeng Zhang (China Agricultural University), Prof Zhongxin Chen (Institute of Agriculture Resources & Regional Planning, Chinese Academy of Agriculture Science ),Dr Xinying Xu (Taiyuan University of Technology) Project start date: 1 April 2018 Duration: 10 months Project Summary: Household-based small farms (HBSF) contribute to 96% of agriculture workers in China, 24% of the population. Suffering from low productivity, low efficiency and lack of knowledge/technology for sustainable development, especially in coping with limited resources and environmental issues, aging and poorly-educated HBSFs have become a critical problem in China. In recent years, the Science and Technology at Backyard (STB) programme was proposed to support HBSFs to gain technology inputs from universities and research institutes. Though successful in increasing the yield, the migration of STB from villages to higher county/province level is constrained, due mainly to the low-level automation and huge labours requested. Taking STBs in Laoling City and Yangxin County of Shandong Province as case studies, we aim to demonstrate feasible solutions for scaling up village-based STBs to upper level. By introducing remote sensing data and mapping to in-situ observations, associations are established to guide the operations at different stages to significantly reduce the labour cost for data acquisition for automatic estimation of population and yield. Also an audio-call based interface will be introduced in local dialects for more effective communication with HBSFs to fulfil the recommended operations. |
| Collaborator Contribution | UK Partners: Additional staff time, including academic staff, research staff and technical support; Software tools and platforms: The big data framework developed in UoS will be adapted to the project, with other software tools such as ENVI and Deep Learning machine (UoS) China Partners: In addition to the existing data recorded in the past, CAU will provide local knowledge, field survey and validation, where the staff time and access to the data will be critical to the success of the project; CAAS will provide fix-wing UAV and 2 trained technicians for data collection in the experiment region. Two research scientist and one PhD student will work for this project for 2 months. CAAS will also provide GF-1, GF-2 and possibly GF-6 satellite remote sensing data for the study area. The quantitative remote sensing inversion models of crop and land parameters including LAI, crop coverage, biomass, soil moisture from STFC-NSFC Newton fund project and other scientific research projects will be provided to this project for yield estimation. CAAS will also provide logistic supports for project meetings held in Beijing; TYUT will provide access to their sensors and staff time for design automated feedback device to communicate with HBSFs, these will include their staff time and facilities. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Scaling up from Village to County/Province Level to Support Science & Technology Backyard (STB) Programme for Innovation of Chinese Household-Based Small Farms (WK008) |
| Organisation | Mapping Earth Resources Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Jinchang Ren, University of Strathclyde Project Members: Dr Vijay K Vohora (Mapping Earth Resources Ltd), Weifeng Zhang (China Agricultural University), Prof Zhongxin Chen (Institute of Agriculture Resources & Regional Planning, Chinese Academy of Agriculture Science ),Dr Xinying Xu (Taiyuan University of Technology) Project start date: 1 April 2018 Duration: 10 months Project Summary: Household-based small farms (HBSF) contribute to 96% of agriculture workers in China, 24% of the population. Suffering from low productivity, low efficiency and lack of knowledge/technology for sustainable development, especially in coping with limited resources and environmental issues, aging and poorly-educated HBSFs have become a critical problem in China. In recent years, the Science and Technology at Backyard (STB) programme was proposed to support HBSFs to gain technology inputs from universities and research institutes. Though successful in increasing the yield, the migration of STB from villages to higher county/province level is constrained, due mainly to the low-level automation and huge labours requested. Taking STBs in Laoling City and Yangxin County of Shandong Province as case studies, we aim to demonstrate feasible solutions for scaling up village-based STBs to upper level. By introducing remote sensing data and mapping to in-situ observations, associations are established to guide the operations at different stages to significantly reduce the labour cost for data acquisition for automatic estimation of population and yield. Also an audio-call based interface will be introduced in local dialects for more effective communication with HBSFs to fulfil the recommended operations. |
| Collaborator Contribution | UK Partners: Additional staff time, including academic staff, research staff and technical support; Software tools and platforms: The big data framework developed in UoS will be adapted to the project, with other software tools such as ENVI and Deep Learning machine (UoS) China Partners: In addition to the existing data recorded in the past, CAU will provide local knowledge, field survey and validation, where the staff time and access to the data will be critical to the success of the project; CAAS will provide fix-wing UAV and 2 trained technicians for data collection in the experiment region. Two research scientist and one PhD student will work for this project for 2 months. CAAS will also provide GF-1, GF-2 and possibly GF-6 satellite remote sensing data for the study area. The quantitative remote sensing inversion models of crop and land parameters including LAI, crop coverage, biomass, soil moisture from STFC-NSFC Newton fund project and other scientific research projects will be provided to this project for yield estimation. CAAS will also provide logistic supports for project meetings held in Beijing; TYUT will provide access to their sensors and staff time for design automated feedback device to communicate with HBSFs, these will include their staff time and facilities. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Scaling up from Village to County/Province Level to Support Science & Technology Backyard (STB) Programme for Innovation of Chinese Household-Based Small Farms (WK008) |
| Organisation | Taiyuan University of Technology |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Jinchang Ren, University of Strathclyde Project Members: Dr Vijay K Vohora (Mapping Earth Resources Ltd), Weifeng Zhang (China Agricultural University), Prof Zhongxin Chen (Institute of Agriculture Resources & Regional Planning, Chinese Academy of Agriculture Science ),Dr Xinying Xu (Taiyuan University of Technology) Project start date: 1 April 2018 Duration: 10 months Project Summary: Household-based small farms (HBSF) contribute to 96% of agriculture workers in China, 24% of the population. Suffering from low productivity, low efficiency and lack of knowledge/technology for sustainable development, especially in coping with limited resources and environmental issues, aging and poorly-educated HBSFs have become a critical problem in China. In recent years, the Science and Technology at Backyard (STB) programme was proposed to support HBSFs to gain technology inputs from universities and research institutes. Though successful in increasing the yield, the migration of STB from villages to higher county/province level is constrained, due mainly to the low-level automation and huge labours requested. Taking STBs in Laoling City and Yangxin County of Shandong Province as case studies, we aim to demonstrate feasible solutions for scaling up village-based STBs to upper level. By introducing remote sensing data and mapping to in-situ observations, associations are established to guide the operations at different stages to significantly reduce the labour cost for data acquisition for automatic estimation of population and yield. Also an audio-call based interface will be introduced in local dialects for more effective communication with HBSFs to fulfil the recommended operations. |
| Collaborator Contribution | UK Partners: Additional staff time, including academic staff, research staff and technical support; Software tools and platforms: The big data framework developed in UoS will be adapted to the project, with other software tools such as ENVI and Deep Learning machine (UoS) China Partners: In addition to the existing data recorded in the past, CAU will provide local knowledge, field survey and validation, where the staff time and access to the data will be critical to the success of the project; CAAS will provide fix-wing UAV and 2 trained technicians for data collection in the experiment region. Two research scientist and one PhD student will work for this project for 2 months. CAAS will also provide GF-1, GF-2 and possibly GF-6 satellite remote sensing data for the study area. The quantitative remote sensing inversion models of crop and land parameters including LAI, crop coverage, biomass, soil moisture from STFC-NSFC Newton fund project and other scientific research projects will be provided to this project for yield estimation. CAAS will also provide logistic supports for project meetings held in Beijing; TYUT will provide access to their sensors and staff time for design automated feedback device to communicate with HBSFs, these will include their staff time and facilities. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Scaling up from Village to County/Province Level to Support Science & Technology Backyard (STB) Programme for Innovation of Chinese Household-Based Small Farms (WK008) |
| Organisation | University of Strathclyde |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Jinchang Ren, University of Strathclyde Project Members: Dr Vijay K Vohora (Mapping Earth Resources Ltd), Weifeng Zhang (China Agricultural University), Prof Zhongxin Chen (Institute of Agriculture Resources & Regional Planning, Chinese Academy of Agriculture Science ),Dr Xinying Xu (Taiyuan University of Technology) Project start date: 1 April 2018 Duration: 10 months Project Summary: Household-based small farms (HBSF) contribute to 96% of agriculture workers in China, 24% of the population. Suffering from low productivity, low efficiency and lack of knowledge/technology for sustainable development, especially in coping with limited resources and environmental issues, aging and poorly-educated HBSFs have become a critical problem in China. In recent years, the Science and Technology at Backyard (STB) programme was proposed to support HBSFs to gain technology inputs from universities and research institutes. Though successful in increasing the yield, the migration of STB from villages to higher county/province level is constrained, due mainly to the low-level automation and huge labours requested. Taking STBs in Laoling City and Yangxin County of Shandong Province as case studies, we aim to demonstrate feasible solutions for scaling up village-based STBs to upper level. By introducing remote sensing data and mapping to in-situ observations, associations are established to guide the operations at different stages to significantly reduce the labour cost for data acquisition for automatic estimation of population and yield. Also an audio-call based interface will be introduced in local dialects for more effective communication with HBSFs to fulfil the recommended operations. |
| Collaborator Contribution | UK Partners: Additional staff time, including academic staff, research staff and technical support; Software tools and platforms: The big data framework developed in UoS will be adapted to the project, with other software tools such as ENVI and Deep Learning machine (UoS) China Partners: In addition to the existing data recorded in the past, CAU will provide local knowledge, field survey and validation, where the staff time and access to the data will be critical to the success of the project; CAAS will provide fix-wing UAV and 2 trained technicians for data collection in the experiment region. Two research scientist and one PhD student will work for this project for 2 months. CAAS will also provide GF-1, GF-2 and possibly GF-6 satellite remote sensing data for the study area. The quantitative remote sensing inversion models of crop and land parameters including LAI, crop coverage, biomass, soil moisture from STFC-NSFC Newton fund project and other scientific research projects will be provided to this project for yield estimation. CAAS will also provide logistic supports for project meetings held in Beijing; TYUT will provide access to their sensors and staff time for design automated feedback device to communicate with HBSFs, these will include their staff time and facilities. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Scoping an Information Management System for Chinese Agriculture (Small Project Award: WK003) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Lucy Wilson (RSK ADAS) Project Members: Dr Zhigang Liu (Courtyard Agriculture Ltd), Wang Hao (VIPFarms), Hainie Zha (China Agricultural University) Project start date: 1 April 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | VIPFarms will provide in the region of 10-15 working days of in-kind contribution. China Agriculture University will provide a similar amount of time to advise, support, review outputs; organise a workshop and take the mock-ups out to Xushui STB to obtain feedback on the draft versions. Both will provide technical support. |
| Impact | Recommendations for follow up activities to this scoping study are; 1. Carry out further social research on the drivers and barriers for agronomic decisions and what could influence change in practice. 2. Further investigation into apps for Chinese farming that are in existence or in the latter stages of development and the data requirements thereof. 3. Development of a more sophisticated prototype with end user involvement, including testing. These are to be addressed as part of the Quzhou Agri-Tech Integration Programme. |
| Start Year | 2018 |
| Description | Scoping an Information Management System for Chinese Agriculture (Small Project Award: WK003) |
| Organisation | Courtyard Agriculture Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Lucy Wilson (RSK ADAS) Project Members: Dr Zhigang Liu (Courtyard Agriculture Ltd), Wang Hao (VIPFarms), Hainie Zha (China Agricultural University) Project start date: 1 April 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | VIPFarms will provide in the region of 10-15 working days of in-kind contribution. China Agriculture University will provide a similar amount of time to advise, support, review outputs; organise a workshop and take the mock-ups out to Xushui STB to obtain feedback on the draft versions. Both will provide technical support. |
| Impact | Recommendations for follow up activities to this scoping study are; 1. Carry out further social research on the drivers and barriers for agronomic decisions and what could influence change in practice. 2. Further investigation into apps for Chinese farming that are in existence or in the latter stages of development and the data requirements thereof. 3. Development of a more sophisticated prototype with end user involvement, including testing. These are to be addressed as part of the Quzhou Agri-Tech Integration Programme. |
| Start Year | 2018 |
| Description | Scoping an Information Management System for Chinese Agriculture (Small Project Award: WK003) |
| Organisation | RSK ADAS Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Lucy Wilson (RSK ADAS) Project Members: Dr Zhigang Liu (Courtyard Agriculture Ltd), Wang Hao (VIPFarms), Hainie Zha (China Agricultural University) Project start date: 1 April 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | VIPFarms will provide in the region of 10-15 working days of in-kind contribution. China Agriculture University will provide a similar amount of time to advise, support, review outputs; organise a workshop and take the mock-ups out to Xushui STB to obtain feedback on the draft versions. Both will provide technical support. |
| Impact | Recommendations for follow up activities to this scoping study are; 1. Carry out further social research on the drivers and barriers for agronomic decisions and what could influence change in practice. 2. Further investigation into apps for Chinese farming that are in existence or in the latter stages of development and the data requirements thereof. 3. Development of a more sophisticated prototype with end user involvement, including testing. These are to be addressed as part of the Quzhou Agri-Tech Integration Programme. |
| Start Year | 2018 |
| Description | Space Robotic Technologies for Plant Grafting (Small Project Award: WK005) |
| Organisation | China Academy of Launch Vehicle Technology |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiu Yan (University of Strathclyde) Project Members: Dr Zhiyuan Yu (China Academy of Launch Vehicle Technology), Dr Yue Shen (Jiangsu University), Dr Chaochun Zhang (China Agricultural University), Dr. Xiaoyong Sun (Shandong Agricultural University) Project start date: 1 May 2018 Duration: 10 months Project Summary: 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. |
| Collaborator Contribution | The data analysis team is supported by NSFC grant and have free access to national supercomputing center in Guangdong (Tianhe 2) and national supercomputing center in Shandong. Agricultural big data center in Shandong province will provide related server and tools for further analysis; China Agriculture University has set up a Science and Technology Backyard in Houlaoying Village where watermelon is widely growing. Those works help us take insight into the current problem of watermelon producing to which the farmers commonly face up, and we also build up experiences on watermelon grafting. There are other grants available for supporting the associated studies. CALT can provide Adjusting and Testing equipment for grafting robotic devices, arm and unmanned ground vehicle. The design controller tools and software are supported by NSFC grant. Jiangsu University will provide related components and analysis capability. Strathclyde University will provide robotic equipment in supporting this project. In addition, Space Mechatronics Systems Technologies (SMeSTech) Lab has over ten robots which could be used to support this project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Space Robotic Technologies for Plant Grafting (Small Project Award: WK005) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiu Yan (University of Strathclyde) Project Members: Dr Zhiyuan Yu (China Academy of Launch Vehicle Technology), Dr Yue Shen (Jiangsu University), Dr Chaochun Zhang (China Agricultural University), Dr. Xiaoyong Sun (Shandong Agricultural University) Project start date: 1 May 2018 Duration: 10 months Project Summary: 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. |
| Collaborator Contribution | The data analysis team is supported by NSFC grant and have free access to national supercomputing center in Guangdong (Tianhe 2) and national supercomputing center in Shandong. Agricultural big data center in Shandong province will provide related server and tools for further analysis; China Agriculture University has set up a Science and Technology Backyard in Houlaoying Village where watermelon is widely growing. Those works help us take insight into the current problem of watermelon producing to which the farmers commonly face up, and we also build up experiences on watermelon grafting. There are other grants available for supporting the associated studies. CALT can provide Adjusting and Testing equipment for grafting robotic devices, arm and unmanned ground vehicle. The design controller tools and software are supported by NSFC grant. Jiangsu University will provide related components and analysis capability. Strathclyde University will provide robotic equipment in supporting this project. In addition, Space Mechatronics Systems Technologies (SMeSTech) Lab has over ten robots which could be used to support this project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Space Robotic Technologies for Plant Grafting (Small Project Award: WK005) |
| Organisation | Jiangsu University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiu Yan (University of Strathclyde) Project Members: Dr Zhiyuan Yu (China Academy of Launch Vehicle Technology), Dr Yue Shen (Jiangsu University), Dr Chaochun Zhang (China Agricultural University), Dr. Xiaoyong Sun (Shandong Agricultural University) Project start date: 1 May 2018 Duration: 10 months Project Summary: 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. |
| Collaborator Contribution | The data analysis team is supported by NSFC grant and have free access to national supercomputing center in Guangdong (Tianhe 2) and national supercomputing center in Shandong. Agricultural big data center in Shandong province will provide related server and tools for further analysis; China Agriculture University has set up a Science and Technology Backyard in Houlaoying Village where watermelon is widely growing. Those works help us take insight into the current problem of watermelon producing to which the farmers commonly face up, and we also build up experiences on watermelon grafting. There are other grants available for supporting the associated studies. CALT can provide Adjusting and Testing equipment for grafting robotic devices, arm and unmanned ground vehicle. The design controller tools and software are supported by NSFC grant. Jiangsu University will provide related components and analysis capability. Strathclyde University will provide robotic equipment in supporting this project. In addition, Space Mechatronics Systems Technologies (SMeSTech) Lab has over ten robots which could be used to support this project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Space Robotic Technologies for Plant Grafting (Small Project Award: WK005) |
| Organisation | Shandong Agricultural University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiu Yan (University of Strathclyde) Project Members: Dr Zhiyuan Yu (China Academy of Launch Vehicle Technology), Dr Yue Shen (Jiangsu University), Dr Chaochun Zhang (China Agricultural University), Dr. Xiaoyong Sun (Shandong Agricultural University) Project start date: 1 May 2018 Duration: 10 months Project Summary: 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. |
| Collaborator Contribution | The data analysis team is supported by NSFC grant and have free access to national supercomputing center in Guangdong (Tianhe 2) and national supercomputing center in Shandong. Agricultural big data center in Shandong province will provide related server and tools for further analysis; China Agriculture University has set up a Science and Technology Backyard in Houlaoying Village where watermelon is widely growing. Those works help us take insight into the current problem of watermelon producing to which the farmers commonly face up, and we also build up experiences on watermelon grafting. There are other grants available for supporting the associated studies. CALT can provide Adjusting and Testing equipment for grafting robotic devices, arm and unmanned ground vehicle. The design controller tools and software are supported by NSFC grant. Jiangsu University will provide related components and analysis capability. Strathclyde University will provide robotic equipment in supporting this project. In addition, Space Mechatronics Systems Technologies (SMeSTech) Lab has over ten robots which could be used to support this project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Space Robotic Technologies for Plant Grafting (Small Project Award: WK005) |
| Organisation | University of Strathclyde |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Xiu Yan (University of Strathclyde) Project Members: Dr Zhiyuan Yu (China Academy of Launch Vehicle Technology), Dr Yue Shen (Jiangsu University), Dr Chaochun Zhang (China Agricultural University), Dr. Xiaoyong Sun (Shandong Agricultural University) Project start date: 1 May 2018 Duration: 10 months Project Summary: 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. |
| Collaborator Contribution | The data analysis team is supported by NSFC grant and have free access to national supercomputing center in Guangdong (Tianhe 2) and national supercomputing center in Shandong. Agricultural big data center in Shandong province will provide related server and tools for further analysis; China Agriculture University has set up a Science and Technology Backyard in Houlaoying Village where watermelon is widely growing. Those works help us take insight into the current problem of watermelon producing to which the farmers commonly face up, and we also build up experiences on watermelon grafting. There are other grants available for supporting the associated studies. CALT can provide Adjusting and Testing equipment for grafting robotic devices, arm and unmanned ground vehicle. The design controller tools and software are supported by NSFC grant. Jiangsu University will provide related components and analysis capability. Strathclyde University will provide robotic equipment in supporting this project. In addition, Space Mechatronics Systems Technologies (SMeSTech) Lab has over ten robots which could be used to support this project. |
| Impact | Information pending completion of project |
| Start Year | 2018 |
| Description | Translating UK expertise in viticulture weather risk analysis into sustainable vineyard management tools for vineyards in China. (Pathfinder Award: PF003) |
| Organisation | Climate Wine Consulting Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project Lead(s): Dr. Alistair Nesbitt (Climate Wine Consulting Ltd) Project Members: Dr. Xu Liu (Northwest Agriculture and Forestry University) Project start date: 1 August 2017 Duration: One month Project Summary: The aim of this Pathfinder project was to work with the North West University of Agriculture and Forestry (NWAFU) College of Enology (wine science) to assess the potential for, and advantages of automated and remote environmental data capture as vineyard management tools. Through data capture and analysis vineyard management can be directed to increase sustainability and reduce inputs. For the Pathfinder project, this entailed: 1) Evaluating the availability and quality of existing topographical, soil moisture, and historic weather data-sets for key vineyard areas. 2) Analysing the value of a series of temperature, relative humidity and soil-moisture sensors in three pilot vineyards. 3) Mapping the three pilot vineyards using GIS and satellite or air-borne derived geo-spatial data to model topography and frost risk as case-studies (the 3 vineyards were Pernod Ricard's Helan Mountain vineyards, Chateau Moser, and Cheng Cheng vineyard - also in the Helan Mountain region of Xianling). 4) Evaluating (desk-top) existing vineyard frost protection technology, uptake and efficacy. 5) Co-developing, with the NWUAF and vineyard managers, a case for funding for a substantial project to deliver data-driven decision-making tools regarding irrigation and frost protection, for Chinese viticulture. |
| Collaborator Contribution | The NWAFU College of Enology will contribute 5 full days of staff time, provide accommodation for Dr. Nesbitt from CWC on a 5 day visit to China, will provide meeting room space at the University, will organise and promote a meeting with growers through its network, and will provide in-kind translation facilities for project output. Additionally, the International Organisation for Vine and Wine Asian Grape and Wine Technology Development Center, the International Federation of Wine Universities, the Shaanxi Province's grape and wine Engineering Research Center, and the sub-branch of Wine and Grapes of the Shaanxi Fruit Industry Association, are all located at the NWAFU College of Enology who will facilitate access to their dissemination channels. |
| Impact | Future collaboration with NWUAF agreed on two fronts; 1. Provide a short but intensive training course to the College of Enology students on climate change and environmental risks and on the use of GIS as decision support tools in a vineyard environment. 2. Begin a viticulture climate and terrain modelling project on the Helan Mountain area with a student and Prof. Xu Liu. This would include developing a business case for collating existing and future weather and terrain data for vineyard areas into a centralised repository held by the university. Build a business case to supply historic and real-time weather, soil-moisture and plant growth data to vineyards in the Helan Mountain areas as part of a vineyard decision support tool package - evidencing benefits. Provide a case-study of how GIS, in-site weather data and remote / satellite data could be used to inform irrigation decisions and aid in identifying frost risk zones and areas for protection. Use this to inform a bid for further funding to commence provision of frost and irrigation services. Propose a business service to provide these (topographic, weather and near real-time soil moisture) mapping and data provision to existing and future vineyards. Also provide training at the university on modelling frost risk. Showcase frost protection technology and market in China. Provide information to viticulture students on frost protection and its economic benefits. Seek funding to translate a presentation of frost protection strategies into Chinese and place on the CWC and NWUAF websites. |
| Start Year | 2017 |
| Description | Translating UK expertise in viticulture weather risk analysis into sustainable vineyard management tools for vineyards in China. (Pathfinder Award: PF003) |
| Organisation | North West Agriculture and Forestry University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr. Alistair Nesbitt (Climate Wine Consulting Ltd) Project Members: Dr. Xu Liu (Northwest Agriculture and Forestry University) Project start date: 1 August 2017 Duration: One month Project Summary: The aim of this Pathfinder project was to work with the North West University of Agriculture and Forestry (NWAFU) College of Enology (wine science) to assess the potential for, and advantages of automated and remote environmental data capture as vineyard management tools. Through data capture and analysis vineyard management can be directed to increase sustainability and reduce inputs. For the Pathfinder project, this entailed: 1) Evaluating the availability and quality of existing topographical, soil moisture, and historic weather data-sets for key vineyard areas. 2) Analysing the value of a series of temperature, relative humidity and soil-moisture sensors in three pilot vineyards. 3) Mapping the three pilot vineyards using GIS and satellite or air-borne derived geo-spatial data to model topography and frost risk as case-studies (the 3 vineyards were Pernod Ricard's Helan Mountain vineyards, Chateau Moser, and Cheng Cheng vineyard - also in the Helan Mountain region of Xianling). 4) Evaluating (desk-top) existing vineyard frost protection technology, uptake and efficacy. 5) Co-developing, with the NWUAF and vineyard managers, a case for funding for a substantial project to deliver data-driven decision-making tools regarding irrigation and frost protection, for Chinese viticulture. |
| Collaborator Contribution | The NWAFU College of Enology will contribute 5 full days of staff time, provide accommodation for Dr. Nesbitt from CWC on a 5 day visit to China, will provide meeting room space at the University, will organise and promote a meeting with growers through its network, and will provide in-kind translation facilities for project output. Additionally, the International Organisation for Vine and Wine Asian Grape and Wine Technology Development Center, the International Federation of Wine Universities, the Shaanxi Province's grape and wine Engineering Research Center, and the sub-branch of Wine and Grapes of the Shaanxi Fruit Industry Association, are all located at the NWAFU College of Enology who will facilitate access to their dissemination channels. |
| Impact | Future collaboration with NWUAF agreed on two fronts; 1. Provide a short but intensive training course to the College of Enology students on climate change and environmental risks and on the use of GIS as decision support tools in a vineyard environment. 2. Begin a viticulture climate and terrain modelling project on the Helan Mountain area with a student and Prof. Xu Liu. This would include developing a business case for collating existing and future weather and terrain data for vineyard areas into a centralised repository held by the university. Build a business case to supply historic and real-time weather, soil-moisture and plant growth data to vineyards in the Helan Mountain areas as part of a vineyard decision support tool package - evidencing benefits. Provide a case-study of how GIS, in-site weather data and remote / satellite data could be used to inform irrigation decisions and aid in identifying frost risk zones and areas for protection. Use this to inform a bid for further funding to commence provision of frost and irrigation services. Propose a business service to provide these (topographic, weather and near real-time soil moisture) mapping and data provision to existing and future vineyards. Also provide training at the university on modelling frost risk. Showcase frost protection technology and market in China. Provide information to viticulture students on frost protection and its economic benefits. Seek funding to translate a presentation of frost protection strategies into Chinese and place on the CWC and NWUAF websites. |
| Start Year | 2017 |
| Description | UAV tracking system for pollinators (Small Project Award: SM024) |
| Organisation | Bangor University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Paul Cross (Bangor University) Project Members: Dr Cristiano Palego (Bangor University), Dr Chaochun Zhang and Prof Fusuo Zhang (China Agricultural University) Project start date: 1 July 2018 Duration: Six months Project Summary: Validation of the effectiveness of a novel tracking device for insect pollinators across their entire foraging range. |
| Collaborator Contribution | Bangor University will supply the drones, technical support and requisite skills transfer to the Chinese colleague for the tracking of pollinators in the field sites. China Agricultural University will provide one STB for the research platform of this project. The university will also supply technical support for necessary analysis of any soil and plant samples collected from the field site. |
| Impact | Tracking technology presented by Dr Paul Cross to a seminar at China Agricultural University and the Bee Research Institute CAAS, BBC Countryfile (26th August 2018), BIBBA conference (6th September 2018), Cirencester, UK. Interview with local Chinese media to explain the objectives of the project: https://mp.weixin.qq.com/s/s2V47ce0yvtKtMxg1h3T1g?fbclid=IwAR1CD16o1MbErc79lLNE_RN6KlR_Ti9g5i4QcPKBnKZ8f2bp4GSn4LGZtkw |
| Start Year | 2018 |
| Description | UAV tracking system for pollinators (Small Project Award: SM024) |
| Organisation | China Agricultural University (CAU) |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Paul Cross (Bangor University) Project Members: Dr Cristiano Palego (Bangor University), Dr Chaochun Zhang and Prof Fusuo Zhang (China Agricultural University) Project start date: 1 July 2018 Duration: Six months Project Summary: Validation of the effectiveness of a novel tracking device for insect pollinators across their entire foraging range. |
| Collaborator Contribution | Bangor University will supply the drones, technical support and requisite skills transfer to the Chinese colleague for the tracking of pollinators in the field sites. China Agricultural University will provide one STB for the research platform of this project. The university will also supply technical support for necessary analysis of any soil and plant samples collected from the field site. |
| Impact | Tracking technology presented by Dr Paul Cross to a seminar at China Agricultural University and the Bee Research Institute CAAS, BBC Countryfile (26th August 2018), BIBBA conference (6th September 2018), Cirencester, UK. Interview with local Chinese media to explain the objectives of the project: https://mp.weixin.qq.com/s/s2V47ce0yvtKtMxg1h3T1g?fbclid=IwAR1CD16o1MbErc79lLNE_RN6KlR_Ti9g5i4QcPKBnKZ8f2bp4GSn4LGZtkw |
| Start Year | 2018 |
| Description | Using Sentinel data for drought monitoring (Small Project Award: SM007) |
| Organisation | Peking University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Kevin Tansey and Dr Darren Ghent (University of Leicester) Project Members: Dr Emma Dodd (University of Leicester), Prof Huazhong Ren (China Lead, Peking University), Prof Lei Yan, Mr Yitong Zheng, Mr Xingbang Hu, Miss Mingzhu Guo, Prof Hongying Zhao and Mr Haimeng Zhao (Peking University) Project start date: 15 Feb 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof. Tansey will be supported to attend the workshop under the Chinese Government SAFE programme which he is involved with. He is required to spend up to 30 days in China each year for the next 3 years. This is an in-kind contribution of approximately £5000/year by the Chinese. Dr Ghent is PI of the GlobTemperature project and is also a member of the UK's National Centre for Earth Observation who will note that this activity is taking place. There is further interest with LST being recognised as a Essential Climate Variable so will be part of further projects based at the University of Leicester. Dr. Ren of PKU in currently working on the National High-Resolution Earth Observation Project of China. This means that Dr. Ren will be able to get Gaofen-5 thermal infrared images. Dr. Ren has developed algorithms to retrieve LST from Landsat 8 and Chinese Gaofen-5 and estimate narrowband and broadband emissivity, and has a UAV system (DJ M600) with both thermal infrared camera and VNIR camera. Besides, Dr. Ren also has established three LST ground-measurement sites in Hebei, Henan and Inner Mongolia of China. These systems will ensure the LST evaluation in this project. Moreover, Dr. Ren's group has some contribution in the agricultural drought monitoring. Associate Professor Zhao's group at PKU will contribute support and time for the UAV image analysis and data collection. He will ensure complete UAV remote sensing experiments. |
| Impact | Science questions to develop in the future: 1. Can we use the remote sensing BIGDATA from ESA and China to improve the accuracy of crop and environment monitoring in Asia and European? 2. Can we utilise a combination of satellites at different spatial / temporal resolutions (such as Sentinel-3, Gaofen-5, FY-2) to better quantify drought indices for agricultural monitoring? 3. Can we enhance capabilities in land and atmospheric modelling with novel space borne datasets for parameter estimate and crop monitoring? 4. In more heterogeneous landscapes can we utilise multiple data streams to improve the upscaling of ground-based measurements to the scale of the satellite pixel? 5. To extend the scope of existing partnerships and facilitate new communication streams with Chinese partners enabling integration of science expertise Planned data transfer/exchanges: 1. Setup a long-term exchange of Sentinel-3 satellite extractions over China and in situ data from Chinese validation sites 2. Objective to keep the exchange of data going for at least a year or more in order to investigate the seasonal and monthly differences, which are very important for crop monitoring 3. Gaofen-5 data exchanges once available |
| Start Year | 2018 |
| Description | Using Sentinel data for drought monitoring (Small Project Award: SM007) |
| Organisation | University of Leicester |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Prof Kevin Tansey and Dr Darren Ghent (University of Leicester) Project Members: Dr Emma Dodd (University of Leicester), Prof Huazhong Ren (China Lead, Peking University), Prof Lei Yan, Mr Yitong Zheng, Mr Xingbang Hu, Miss Mingzhu Guo, Prof Hongying Zhao and Mr Haimeng Zhao (Peking University) Project start date: 15 Feb 2018 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | Prof. Tansey will be supported to attend the workshop under the Chinese Government SAFE programme which he is involved with. He is required to spend up to 30 days in China each year for the next 3 years. This is an in-kind contribution of approximately £5000/year by the Chinese. Dr Ghent is PI of the GlobTemperature project and is also a member of the UK's National Centre for Earth Observation who will note that this activity is taking place. There is further interest with LST being recognised as a Essential Climate Variable so will be part of further projects based at the University of Leicester. Dr. Ren of PKU in currently working on the National High-Resolution Earth Observation Project of China. This means that Dr. Ren will be able to get Gaofen-5 thermal infrared images. Dr. Ren has developed algorithms to retrieve LST from Landsat 8 and Chinese Gaofen-5 and estimate narrowband and broadband emissivity, and has a UAV system (DJ M600) with both thermal infrared camera and VNIR camera. Besides, Dr. Ren also has established three LST ground-measurement sites in Hebei, Henan and Inner Mongolia of China. These systems will ensure the LST evaluation in this project. Moreover, Dr. Ren's group has some contribution in the agricultural drought monitoring. Associate Professor Zhao's group at PKU will contribute support and time for the UAV image analysis and data collection. He will ensure complete UAV remote sensing experiments. |
| Impact | Science questions to develop in the future: 1. Can we use the remote sensing BIGDATA from ESA and China to improve the accuracy of crop and environment monitoring in Asia and European? 2. Can we utilise a combination of satellites at different spatial / temporal resolutions (such as Sentinel-3, Gaofen-5, FY-2) to better quantify drought indices for agricultural monitoring? 3. Can we enhance capabilities in land and atmospheric modelling with novel space borne datasets for parameter estimate and crop monitoring? 4. In more heterogeneous landscapes can we utilise multiple data streams to improve the upscaling of ground-based measurements to the scale of the satellite pixel? 5. To extend the scope of existing partnerships and facilitate new communication streams with Chinese partners enabling integration of science expertise Planned data transfer/exchanges: 1. Setup a long-term exchange of Sentinel-3 satellite extractions over China and in situ data from Chinese validation sites 2. Objective to keep the exchange of data going for at least a year or more in order to investigate the seasonal and monthly differences, which are very important for crop monitoring 3. Gaofen-5 data exchanges once available |
| Start Year | 2018 |
| Description | Wheat rust and wheat growth modelling workshop (Intra-Project Partnership Award: IPP002) |
| Organisation | Centre for Agriculture and Bioscience International |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Project Lead(s): Belinda Luke (CABI) Project Members: Prof Wenjiang Huang (Chinese Academy of Sciences) Project start date: 9 Jan 2018 Duration: Four months Project Summary: To hold a two-day workshop with leading experts on wheat rust and wheat growth modelling and earth observation. |
| Collaborator Contribution | The in-kind contribution from the Chinese partners will be staff time in attending the workshop and helping to write the output publication |
| Impact | As a result of the workshop an outline draft of a review paper was prepared which covered the current modelling approaches to predicting P. striiformis f. sp. tritici, in addition to how EO data may be used to improve this. All workshop participants have been offered the opportunity to contribute to the paper and joint authorship. The paper is currently in draft form and once a draft is finalised, the paper will be submitted to an appropriate journal as an open access paper. |
| Start Year | 2018 |
| Description | Wheat rust and wheat growth modelling workshop (Intra-Project Partnership Award: IPP002) |
| Organisation | Chinese Academy of Sciences |
| Country | China |
| Sector | Public |
| PI Contribution | Project Lead(s): Belinda Luke (CABI) Project Members: Prof Wenjiang Huang (Chinese Academy of Sciences) Project start date: 9 Jan 2018 Duration: Four months Project Summary: To hold a two-day workshop with leading experts on wheat rust and wheat growth modelling and earth observation. |
| Collaborator Contribution | The in-kind contribution from the Chinese partners will be staff time in attending the workshop and helping to write the output publication |
| Impact | As a result of the workshop an outline draft of a review paper was prepared which covered the current modelling approaches to predicting P. striiformis f. sp. tritici, in addition to how EO data may be used to improve this. All workshop participants have been offered the opportunity to contribute to the paper and joint authorship. The paper is currently in draft form and once a draft is finalised, the paper will be submitted to an appropriate journal as an open access paper. |
| Start Year | 2018 |
| Description | Yield forecasting systems and early blight detection of potato crops in China (Proof-of-Concept Award: PC010) |
| Organisation | China Centre for Resources Satellite Data and Application |
| Country | China |
| Sector | Public |
| PI Contribution | Project Lead(s): Dr Bo Li - NIAB EMR Project Members:Dr Jane Thomas (NIAB); Dr Marc Allison (NIAB CUF); Dr Toby Waine (Cranfield University); Mr Weijian Sun (China Center for Resources Satellite Date & Application (CRESDA)), Mr Qingji Meng (Beijing Yagro Navitech) Project start date: 1 May 2017 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | NIAB CUF will supply their commercial potato yield forecasting service (YieldCheck) and the Smartphone software (CanopyCheck). NIAB-CUF will also provide expertise in ground-truthing remotely sensed data and its integration into yield forecasting systems. NIAB will provide potato trial plots used as a PhD project on the study of early blight and the crop will also be scanned by drone imaging for yield prediction. CRESDA will provide multispectral satellite images of the potato crops in China Beijing Yagro Navitech will GPS locations of the potato crop also the final yield data measured by local farmer. |
| Impact | Newton grant proposal developed which aimed to develop an expert support platform for Chinese potato industry with applying remote sensing to late blight disease management, yield forecast and potato seed quality control. This Newton grant application has been submitted with CRESDA, IVF CAAS, RADI CAS and Xisen potato as Chinese academic and industrial partners and Agrimetrics and Outfield as British industrial partners |
| Start Year | 2017 |
| Description | Yield forecasting systems and early blight detection of potato crops in China (Proof-of-Concept Award: PC010) |
| Organisation | Cranfield University |
| Department | Centre for Environment and Agricultural Informatics |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Bo Li - NIAB EMR Project Members:Dr Jane Thomas (NIAB); Dr Marc Allison (NIAB CUF); Dr Toby Waine (Cranfield University); Mr Weijian Sun (China Center for Resources Satellite Date & Application (CRESDA)), Mr Qingji Meng (Beijing Yagro Navitech) Project start date: 1 May 2017 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | NIAB CUF will supply their commercial potato yield forecasting service (YieldCheck) and the Smartphone software (CanopyCheck). NIAB-CUF will also provide expertise in ground-truthing remotely sensed data and its integration into yield forecasting systems. NIAB will provide potato trial plots used as a PhD project on the study of early blight and the crop will also be scanned by drone imaging for yield prediction. CRESDA will provide multispectral satellite images of the potato crops in China Beijing Yagro Navitech will GPS locations of the potato crop also the final yield data measured by local farmer. |
| Impact | Newton grant proposal developed which aimed to develop an expert support platform for Chinese potato industry with applying remote sensing to late blight disease management, yield forecast and potato seed quality control. This Newton grant application has been submitted with CRESDA, IVF CAAS, RADI CAS and Xisen potato as Chinese academic and industrial partners and Agrimetrics and Outfield as British industrial partners |
| Start Year | 2017 |
| Description | Yield forecasting systems and early blight detection of potato crops in China (Proof-of-Concept Award: PC010) |
| Organisation | National Institute of Agronomy and Botany (NIAB) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project Lead(s): Dr Bo Li - NIAB EMR Project Members:Dr Jane Thomas (NIAB); Dr Marc Allison (NIAB CUF); Dr Toby Waine (Cranfield University); Mr Weijian Sun (China Center for Resources Satellite Date & Application (CRESDA)), Mr Qingji Meng (Beijing Yagro Navitech) Project start date: 1 May 2017 Duration: Four months Project Summary: 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. |
| Collaborator Contribution | NIAB CUF will supply their commercial potato yield forecasting service (YieldCheck) and the Smartphone software (CanopyCheck). NIAB-CUF will also provide expertise in ground-truthing remotely sensed data and its integration into yield forecasting systems. NIAB will provide potato trial plots used as a PhD project on the study of early blight and the crop will also be scanned by drone imaging for yield prediction. CRESDA will provide multispectral satellite images of the potato crops in China Beijing Yagro Navitech will GPS locations of the potato crop also the final yield data measured by local farmer. |
| Impact | Newton grant proposal developed which aimed to develop an expert support platform for Chinese potato industry with applying remote sensing to late blight disease management, yield forecast and potato seed quality control. This Newton grant application has been submitted with CRESDA, IVF CAAS, RADI CAS and Xisen potato as Chinese academic and industrial partners and Agrimetrics and Outfield as British industrial partners |
| Start Year | 2017 |
| Title | Platform for integrated stress management |
| Description | This product has been developed in collaboration with IBM using a mix of proprietary and bespoke software tools. It provides for the input from multiple sensor and data platforms and links to analytic tools to generate new knowledge related to biotic and abiotic stress factors. The first use case is biota stress resulting from insect pests, but is now being extended to include soil, water and nutrition stresses. |
| Type Of Technology | Software |
| Year Produced | 2018 |
| Open Source License? | Yes |
| Impact | This software has now been adopted as a platform by IBM research in Yorktown for further development. We are in discussion with IBM to explore further exploitation. |
| Description | China-UK Agri-Tech Innovation Partnering Workshop (PC010) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | China-UK Agri-Tech Innovation Partnering Workshop (4-7th July 2017) organized by Innovate UK (iUK) and the Chinese Ministry of Science and Technology (MoST) in Beijing. Dr Lily Zhang, who is working in image analysis group of NIAB EMR attended and established links/potential partners with UK and Chinese experts, including Chinese crop scientists (corn, wheat), remote sensing scientists from RADI and NERCITA (crop disease detection and monitoring, precision agriculture), Agricultural internet entrepreneurs (Da Bei Nong Group) and some companies (eg. agricultural equipment, Industrial base, etc.). |
| Year(s) Of Engagement Activity | 2017 |
| Description | Annual Meeting of the Agri-Tech in China Network+ - Newcastle, UK (20-21 March 2018) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | First Annual Meeting of the Agri-Tech in China Newton Network. The purpose of the meeting is to provide an opportunity to hear about the progress and outcomes of the projects which ATCNN has funded to date, to hear about projects in the wider Network and to look at the opportunities for future UK-China collaboration. |
| Year(s) Of Engagement Activity | 2018 |
| Description | China Needs Analysis Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | A workshop designed to understand the needs of Chinese famers and businesses for UK expertise in relation to agritech in China. This was attended by 115 attendees, around 100 of which from China, with 54 participants from industry. UK and Chinese businesses and academic organisations presented. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Open Innovation Workshop - Beijing, China (5-8 Nov 2017) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The Open Innovation Workshop will develop and fund new UK-China initiatives that use satellite-enabled technologies to address the following: • A system to link satellite data for decision making and resulting recommendations to farmers • A village-level management information system that uses satellite and UAV-derived data for field-specific precision crop management • A system to delineate management zones, possibly using satellite remote sensing images • Robotic systems for grafting seedlings • County-level strategies and technologies for precision crop management |
| Year(s) Of Engagement Activity | 2017 |
| Description | Pathway projects |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | The Network+ funded 5 Pathway Project that supported the development of joint research projects between UK and China and involving public-private partnerships in both countries |
| Year(s) Of Engagement Activity | 2016 |
| Description | Proof of Concept Projects |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | We funded 5 joint UK-China projects to deliver products/impact in rural China through the support of agricultural development. these projects involved both UK and Chinese businesses and academic organisations |
| Year(s) Of Engagement Activity | 2016 |
| Description | STFC project partner workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Supporters |
| Results and Impact | A workshop involving the organisations funded by the STFC to undertake major projects on agritech in China. The purpose was to identify opportunities for coordination and added value. |
| Year(s) Of Engagement Activity | 2016 |
| Description | UK Capabilities Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | A workshop to bring together all interested academic and business groups interested in collaborating on agritech in China. Around 110 attendees, roughly 50% of which were from the business community |
| Year(s) Of Engagement Activity | 2016 |
| Description | Vertical-looking Entomological Radar (VLR) Summer School - Xilinhot, Inner Mongolia (Summer 2018) (Intra-Project Partnership Award: IPP001) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | 20 students, mainly from the Chinese Academy of Agricultural Sciences (CAAS) and Nanjing Agricultural University (NAU), along with Chinese radar and aerial ecology experts from these institutions. The Summer School will provide a fantastic opportunity for knowledge exchange and capacity building amongst the Chinese entomological community. They will be shown how the radar operates, undertake ground-truthing fieldwork and and how to analyse data collected. They will also be trained in other survey techniques for insects (light trapping, hand netting, transects, etc.), and taught how to identify different groups of invertebrates. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Wheat rust and wheat growth modelling workshop, CABI Egham site, UK (22-23 March 2018) (Intra-Project Partnership Award: IPP002) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A two-day workshop with leading experts on wheat rust and wheat growth modelling and EO. Aims: • to gather the current state of the art on wheat rust/growth modelling research, • to identify future research priorities, techniques and needs • to explore how the models can be improved using EO data In addition, we want to foster data sharing and collaboration for combined work, particularly among the projects. The topic of the workshop reflects probably the most common interest across all Newton funded projects. Three consortiums work specifically on wheat modelling (i.e. CABI and RADI, UCL and IARRP-CAAS, Newcastle Uni and BAAFS) while the other two projects (Lincoln Uni and CAMS and Loughborough Uni and Beihang Uni) are working on technologies that could be of great value for collecting more accurate and relevant data for the models. 20 participants, 10 from China and 10 from the UK. Ideally, we would like a good cross representation of the five current STFC projects and from external organizations from China and UK (possibly elsewhere) with a leading role in the field. We will also aim to get a good cross section of agronomist, modellers and EO researchers. The outcome of this workshop would be an open access collaborative opinion paper on the topic, better understanding of modelling wheat rust/growth and hopefully sharing of data between projects to make current models more robust. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Workshop on Data Innovations and Sustainability in Agri-food Supply Chains - Henan Province, China (19-20 April 2017) (Pathfinder Award: PF006) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Workshop Objectives - To bring together UK experts in the field of big data and agriculture sustainability with representatives in Chinese agri-food sector and other academics. - To assess the current practice in China on data innovations in the agri-food industry. - To identify opportunities to learn from best practice examples in the UK. - To develop preliminary action points and identify opportunities for further collaboration between Chinese and UK partners. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Workshop: Chinese and UK Manure Management Experts (Small Project Award: SM019) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A workshop was held at the Chinese Agricultural University in Beijing on 23rd April 2018 to explain the functionality of the MANNER-NPK and ALOWANCE Decision Support Tools. The meeting was followed up by a visit to a pig and poultry farm in Quzhou County to help identify similarities and differences between UK and Chinese manure management systems. |
| Year(s) Of Engagement Activity | 2018 |