APP4FARM: Artificial Intelligence Application for Farming

Developing a Decision Support System to allow farmers to monitor nitrogen loss, for efficient management of nitrogen-based fertilisers.

APP4FARM is a European research project aiming to develop agri-food systems enabled by interconnected digital technologies, that are more transparent to consumers, farmers and other stakeholders along the agri-food value chain. Specifically, APP4FARM will create;

A Decision Support System with a dashboard giving the farmer up-to-date information on nitrogen emission levels
A tailored Sensoring System to monitor environment and soil health, including nitrogen-related microbial activity
Machine Learning/Artificial Intelligence forecasting models

Background

Nitrogen is the primary nutrient, critical for the productivity of agricultural ecosystems. Hence, large changes in the availability of nitrogen can lead to severe alterations of the nitrogen cycle in terrestrial ecosystems. The EU Nitrogen Expert Panel, in 2015, proposed an easy-to-use indicator for ‘nitrogen use efficiency’ (NUE), applicable to agricultural land, farms and whole food production–consumption systems (EU Nitrogen Expert Panel, 2015). Currently, NUE estimates the N surplus as the difference between input and output. To understand the losses, the emission related to single farming systems and climatic zones need to be accurately measured and integrated in a Decision Support System (DSS) in order to design better N management strategies aiming at achieving agronomic objectives (farm income, high crop and animal productivity) and environmental objectives (minimal N losses), simultaneously.

Impact

APP4FARM will contribute towards the following societal impacts:

Publicly available monitoring data, ensuring transparency of the supply chain from the very beginning
The data will provide the basis for a "green labelling" project, leading to more traceable, sustainable and healthy food
Limitation of greenhouse gases (N20) and nitrogen oxides (NOx) emissions
Limitation of the atmospheric concentration of ozone (O3) and aerosols (PM10/PM2.5)
Data transparency