Postcode based fertilizer rate recommendation system
Farmers need cost-effective nitrogen (N) rate recommendations (Rx) in order to make better fertilisation decisions and comply with regulations while maintaining production. We provide district-based N rate Rx, allowing farmers and consultants to better understand plants' needs without relying on time-consuming soil tests or costly field sensors. The end user of our services are farmers but we offer our API services to Agribusinesses, who have farmers as their customers and change per request. Currently, we only offer N Rx at the district level, but we also intend to offer P2O5 and K2O Rx at the post-code level across Europe.
Fertilizer is responsible for 3% of global GHG emissions. Inefficient fertilizer use is also to blame for ground water pollution and declining ecosystems. Farmers require better information in order to challenge their own decision and further optimize their fertilizer input. Government authorities, on the other hand, require a system to effectively enforce environmental regulations. For an instance, current practices attempt to control fertilizer use by recommending a blanket rate, for a state or a county. This is a suboptimal solution that also hurts farmers. As a result of this way of control, high-productive lands are penalized, and the potential of those fields remains under-utilised. On the other hand, fertilizer is wasted on low-productive land because the fields are unable to effectively utilize the applied fertilizer.
What if, we knew how much nitrogen a field could efficiently utlize based on its yield potential? Because this leads to better fertilization optimization and less friction in policy enforcement. Because it provides both authorities and farmers with the data-driven information. Using satellite imagery, we developed models that can estimate crop-specific total nitrogen uptake in kg/ha units. Using historical satellite imagery, we can estimate total nitrogen uptake for previous years and and by utilizing those observations we can provide a reasonable recommendation for nitrogen fertilization ahead of the season.
This solution helps farmers. Such information can also assist input manufacturers and retailers in estimating location-based demand, as well as assisting their customers with input purchase decisions and ultimately enable digital sales. Furthermore, as financial institutes are moving towards sustainable financing, they require a reliable matrices to assess the sustainability of their farmer clients', farm operations. We are also working on a solution that can detect over and under fertilized areas and can be used as a reliable matrices for measuring environmental sustainability.