Multisens

Multisensory precision agriculture – improving yield and reducing environmental impact

The primary objective of this project (2011-2015) was to develop and exploit new multi-sensor techniques for optimizing fertilization, weed-, and disease control to improve yields and reduce the N20-emmissions related to wheat production. In more detail, this included the quantification of effects of site-specific fertilization on N2O emissions, and improving an existing system by a multi sensor approach. Further, we developed a robotized solution for effective N2O-measurements in agricultural fields. We constructed image based, cost effective methods for site-specific control of perennial weeds in cereals, and developed techniques for pre-symptomatic disease detection suitable for site-specific fungicide application systems. Finally, we gained knowledge on how interactions between N-requirement, weed infestation and diseases may influence a site-specific management of fertilizer, herbicides and fungicides.