The research within Agricolus is aimed at the development of new features and solutions that meet the demands of the market of Agriculture 4.0 and the needs of all stakeholders in the food chain, from farmers to food processing companies.

As a matter of fact, Agricolus is a technological partner of several international projects:

  • Horizon 2020 projects, now Horizon Europe
  • Innovation projects such as RisingFoodStars of EIT Food
  • Projects with European organizations (Fiware, NGOs)

The three macro areas of industrial research

Forecasting models

MODELLI previsionali

Earth observation


International projects for Agriculture 4.0


Forecasting models

is an H2020 project that involves a large-scale deployment of Smart Farming platforms implemented through a series of 20 pilot projects in 18 countries. Agricolus is one of 60 partners involved for the aspect related to defense and DSS for olive.


Forecasting models

WATERAGRI is an H2020 project to develop sustainable solutions for water resource conservation and nutrient recycling.


Sustainability and blockchain

Sharebeef is a project promoted by IoF2020 to create shared value within the beef supply chain, involving several European countries. The aim is to improve the productivity and quality of crops for animal nutrition and consequently their health and welfare.

Action for Children


Action for Children in Conflict is a project carried out in Kenya in collaboration with the NGO AfCiC that involves the use of AgriTech tools for rural agriculture in the country.


Earth observation

LINKDAPA is an innovation project, funded by EIT Food, that uses drone and satellite data for the application of typical precision agriculture techniques, such as prescription maps. These maps will be based on the innovative integration of historical and current spatial data sources. In addition, algorithms will be developed to predict maps of potential yield and grain quality (protein), as well as the probability that yield/quality will exceed farmer-specified thresholds in individual grain fields.