Online Decision Support System Fertiliser Optimisation
Creating an online Decision Support system for farmers which processes data from sensors and integrates image analyses to improve both yield quantity and quality.
At the heart of this Flagship Innovation Experiment (FIE) is the objective to process data that are currently not well adapted by the end-user or farmer. In its initial phase this FIE will create the community and the space for cooperation. Subsequently, this FIE develops an online Decision Support System (DSS) using data from sensing platforms to optimise soil management by identifying and localising nutrient input zones. This increases yield quality as well as quantity, hence increasing farmers’ competitiveness. By adapting the content and annotation of various datasets from different sources, the DSS allows for the recording of locally variable environmental conditions and the consequent online integration of processed signals from mobile sensors for site specific fertilising, commonly referred to as variable rate application.
To optimise the models and algorithms applied in this FIE, data on soil, crop and yield from various suppliers are leveraged. Soil and grain properties will be measured by classical methods and proximal probes. To identify cover crops and diagnose the crop status, hyperspectral images from Unmanned Aerial Vehicles (UAVs) and satellites will be subjected to image analysis classification and pattern recognition. The purpose of this FIE’s tool is to increase the technological adaptation by finding correlations between data and modelling, while considering different data exchange standards in machines and agricultural systems. The result will be a DSS, which combines project advisory services with correlation models and methods, based on the content analysis of data.