Background: Timely and large-area information on nutrient concentrations in staple crops is lacking which limits our understanding of how nutrients vary across various geographic areas. In the absence of this information, we cannot efficiently guide research activities dedicated to alleviating potential nutrient deficiencies through genetic biofortification or agronomic biofortification by applying fertilizers.
Overall goal: EO4Nutri will develop innovative scientific solutions that bring together the capabilities of various Earth Observation (EO) data to estimate and predict the nutrient content of the soil, crop canopy, and harvested crops for several global staple grains.
Target crops: maize, rice, sorghum, teff and wheat.
Target nutrients: Calcium (Ca), Iron (Fe), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Potassium (K), Selenium (Se), Sulphur (S), and Zinc (Zn)
The project will focus on two scientific cases: (1) advancing our understanding of the lifecycle of nutrients from the soil to crop canopy and further to crop grains with innovative analytical techniques and EO data, and (2) deepening our understanding of Nitrogen uptake from soil to crop canopy to crop grains and its relationship to grain protein content using Radiative Transfer Models (RTMs) and machine learning methods. The EO4Nutri team will focus on transferring the developed products and datasets into actionable information that can enhance management and decision support systems dedicated to crop nutrient monitoring. Generated scientific results will be integrated into operational activities and a Digital Twin Earth.