INDACAT

Coordinatore di progetto: Università di Milano

Ambiti di ricerca: Ingegneria agraria

Responsabile Scientifico: Patrizia Tassinari

Durata: 12/10/2023 - 12/10/2025

Gruppo di ricerca: Patrizia Tassinari, Valda Rondelli.

In line with the objectives of the European Green Deal, implemented in Italy with the National Plan for Recovery and Resilience (PNRR), there is a growing need for actions to make food production more sustainable, less harmful to the environment and guaranteed to all European citizens. In particular, PNRR point “M2C1 - Sustainable agriculture and circular economy” aims to develop a sustainable agri-food chain, improving the environmental performance and com-petitiveness of farms.

Considering that the livestock sector, and in particular the cattle one, is responsible for a wide share of GHG emissions from the agri-food chain (e.g., methane from enteric fermentation and nitrous oxide from manure storage and man-agement) and that there is still a wide space for improvement in the livestock farms performances, the project INDACAT fits well in the PNRR objectives. INDACAT aims to adopt Precision Livestock Farming (PLF) tools to monitor cows contin-uously under multiple aspects of the whole cattle chain. Each research unit involved will focus on one aspect of cattle farming, and in particular:

- on the barn environment of intensive and organic dairy cattle farms, by monitoring micro-climatic parameters and air quality and adopting data science techniques to model, predict and automatically modify the parameters of the barns in view of improved animals’ welfare,

- on the extensive systems, by monitoring cows’ grazing activities with GIS and IoT technology to identify the spatial position and to make assessments about the grazing activity, feed intake and use of grazing areas (and the related soil degradation) both of dairy cows and cows of the calf-cow line,

- on the social behavior and interactions among cows, by evaluating their behaviors to understand their activities and relationships in view of heat detection, the definition of (re)groupings, detection and/or transmission of diseases, spatial distribution during grazing, health and welfare issues,

- on the growth and weaning of calves, by monitoring calves from their birth to identify an optimal weaning technique that improves animals’ growth, health and welfare finally leading to improved performances in cow ages, and to im-prove knowledge on calves by using technology and data science.

Through INDACAT, overall efficiency improvements will be achieved and will permit the development of a resource-efficient and competitive livestock sector, with positive impacts on the environment, society, and animals’ health and welfare. Farms digitalization will be a key point because the potentialities of PLF (use of sensors, technology, IoT and data science) are huge and widely recognized. By acting on a wide spectrum of cattle livestock aspects, INDACAT will show the potentialities of PLF and data analysis and will clarify how innovation and digitalization can improve the com-petitiveness, sustainability, animal welfare, health and productivity of farms.