Modern agriculture requires decision making criteria applicable to different scales of territory in order to reconcile productivity and respect of the environment, particularly for pest management. Taking into account the recent environmental and European policy constraints, the assessment of the economic profitability of new techniques such as precision agriculture is becoming more and more important.   Site-specific pest management (SSPM) is more than a simple technology, it allows us to increase the relevance of the agronomic decision making criteria according to the environmental management. However, in most cases, the politico-environmental interests are coming up against   economic and socio-economic restraints because the technical results are partially assessed from an economic point of view.

Thus the two main aims of this project are, firstly to elaborate a methodology including farming systems and to define relevant technico-economic indicators to   estimate the profitability of precision agriculture for the total economic activities of the farm. Secondly, to apply this methodology to carry out simulations for representative cropping systems of arable farms in Haute-Normandie.

Our final scale of investigation is the economic farming system.   Three crop systems were selected (cereals, sugar beet-flax and potatoes) and information collected   concerning the technical practices of each crop and the current required input prices. Using standard economic data representative of the region. The economic factors selected were principally production costs and direct profit margin. Using Olympe (economic simulator software) we were able to work at different scales (field, crop system and farm). This methodology allows us to assess different levels of profitability in relation to investments in SSPM equipment required to analyse soil heterogeneity levels. Furthermore, this methodology together with the specialised software has proved their efficiency to assist farmers, agricultural advisers and also regional policy decision-makers.