The need for intensive crop production accompanied by the recent significant increase in fertiliser prices has increased the importance of optimising the use of fertilisers. Nevertheless, farmers tend to use more mineral and organic fertilisers than is biologically necessary, to ensure the highest possible yield. This over-application increases unnecessary application cost, and more importantly, seriously impacts the environment by increasing N leaching, P run off and gaseous losses by volatilisation and denitrification, surface run-off, air, and water pollution and soil acidification.
With ever-decreasing financial margins, but mainly under pressure from growing environmental concerns, a variety of strategies has been deployed in an attempt to mitigate this problem. Precision agriculture is one of the modern methods to optimise the use of nutrients according to the crop needs and soil fertility. It aims to manage within field variability, by deploying site-specific or variable-rate fertilisation technologies, with the objective to apply the right product, and amount of fertilizer in the right time and place, using advanced sensing, modelling and control technologies.
This presentation presented recent findings about the potential of variable rate fertilisation (both synthetic and manure) in arable crop production to increase yield and profitability, with reduced environmental impacts. The approach involves the use of multi-sensor data fusion to map the spatial variability at field scale using remote and proximal sensing technologies. Recommendations for variable rate applications are based on mapping the yield limiting factors. Results of both simulation and field experiments carried out over 10 years in different European and associated countries are reported. Results showed, in the top majority of cases, that variable rate applications increase crop yield by 10%, along with profitability, while reducing environmental impact by reducing the amount of fertilisers applied by up to 20%.
It is recommended to promote the adoption of this technology, as current figures show limited adoption by farmers, and the adoption rate varies among different countries. The limited adoption can be attributed to manifold factors, including the absence of a profitability estimation-based decision support system to guide farmers making a decision on adoption..