Fusion of multi-source and multi-sensor information on soil and crop for optimised crop production system
Project information
Fusion of multi-source and multi-sensor information on soil and crop for optimised crop production systemCall: ICT and Automation for a Greener Agriculture
Id: 14303
Acronym: FarmFUSE
Duration:
Consortium:
| No | Partner | Contact | Country | Total 1000€ | Funded 1000€ | Funder |
|---|---|---|---|---|---|---|
| 1 Coord. | Faculty of bioscience engineering, Ghent University | Abdul Mouazen | Belgium | 303.4 | 214.2 | Department for Environment, Food and Rural Affairs |
| 2 | Agricultural Engineering Laboratory Department of Hydraulics, Soil Science and Agricultural Engineering School of Agriculture Faculty of Agriculture, Forestry and Natural Environment Aristotle University of Thessaloniki | Dimitrios Moshou | Greece | 173.7 | 149.7 | Managing Authority of the Rural Development Plan Ministry of Rural Development & Food |
| 3 | Professorship for Geodesy and Geoinformatics Chair of Geodesy and Geoinformatics Faculty of Agricultural and Environmental Sciences Rostock University | Ralf Bill | Germany | 177.3 | 153.3 | Federal Ministry of Food and Agriculture |
| 4 | Vocational School of Technical Science Uludag University | Yucel Tekin | Turkey | 112.8 | 112.8 | Scientific and Technological Research Council of Turkey |
| 5 | tec5 AG | Steffen Piecha | Germany | 82.3 | 61.7 | Federal Ministry of Food and Agriculture |
| 6 | Professorship for Geodesy and Geoinformatics Chair of Geodesy and Geoinformatics Faculty of Agricultural and Environmental Sciences Rostock University | Jens Wiebensohn | Germany |
Links:
Summary:
Ignoring the inherited spatial variation in soil properties with traditional sampling methods leads to poor crop management, yield loss and excess use of input. The proposed system of FarmFuse addresses these issues in 2 ways: (a) utilising a new and innovative on-line multi-sensor platform for measuring key soil properties at an appropriate resolution. (b) Integrating this improved soil data with other information such as vehicle-borne sensing of crop growth, weather data, soil conductivity and yield maps, to develop algorithms to determine rules for variable rate application. These can then be integrated into FMIS. The vision for the final integrated system would be a server that would allow the end user to access and upload data including maps of soil, crop and yield in addition to recommendations about site specific applications. The resultant treatment maps would then be uploaded to precision agriculture compatible implements for site specific application of inputs.
