R&D&I
We work to contribute our knowledge in climate research, as a pioneer in statistical regionalization, and we offer training for the support and strengthening of scientific capacities.
About the project
Nitrogen is an essential element / nutrient necessary for successful plant growth. Therefore, organic and/or inorganic fertilizers are applied to crops to maintain high yields. When organic fertilizers are applied to the soil, minerals begin to dissolve and the soil releases and absorbs inorganic nitrogen. Applied nitrogen and nitrogen available from crop residues and mineralization of organic matter in the soil is taken up by plants during the growing season, but can also be lost by leaching (mainly as NO3), volatilization or denitrification.
If nitrate is not absorbed by plant roots, it is carried away by runoff or leaches into the soil along with the water and eventually reaches the groundwater. Consumption of groundwater or crops with high nitrate concentrations has negative effects on human health. It is well established that marginal nitrate uptake drops when the optimum nitrogen level is exceeded. Predicting the optimum level of nitrogen addition to a field or parts of a field is therefore a key issue in leaching reduction and one of the objectives of modern precision agriculture. There is a strong relationship between the amount, type and timing of N application and the degree of N leaching and leached nitrate may eventually reach groundwater.
Objectives
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The objective of this project is to demonstrate and implement a service for estimation and prediction of nitrogen content to optimize timing and amounts of fertilization for crops, focusing mainly on cereals. Three crop species in different geographical locations will be evaluated using crop models, soil models, local weather data and weekly/monthly monitoring of crop nitrogen status using satellite imagery.
Reduce fertilizer use by 20-25%, which will increase economic benefits for farmers.
Reduce nitrous oxide emissions and N leaching, thereby reducing global GHG emissions and local water pollution. When accurate information on the current state of nitrogen in the soil is available, the right amount of nitrogen can be made available at any time. There is no need for an uncertainty buffer to avoid scarcity. This will lead to less washing. It can easily mean a reduction of at least 10-15% contamination.
Enable automated post-harvest prediction of soil N content.
Reduce the need for soil testing.
Improve planning of field operations through better local weather forecasts.
To be in line with the concept of precision agriculture with fertilization plan generation.
Funded by
European Union
