INDACAT

In line with the European Green Deal and the Italian National Recovery and Resilience Plan (PNRR), the INDACAT project aims to make cattle farming more sustainable, efficient, and competitive while reducing its environmental impact. Given the significant contribution of the livestock sector to greenhouse gas emissions, the project promotes the adoption of Precision Livestock Farming (PLF) technologies to continuously monitor multiple aspects of the cattle production chain. The project activities focus on monitoring barn environmental conditions, extensive grazing systems, animal social behaviour, and calf growth by integrating sensors, Internet of Things (IoT) technologies, and data analytics to improve animal welfare, farm management, and productivity.

Achieved Results

The overall objective of the project was to investigate the adoption of Precision Livestock Farming (PLF) technologies for the continuous monitoring of dairy cattle throughout the entire livestock production chain and across multiple dimensions, with the ultimate goal of improving the sustainability of the livestock sector. This objective was pursued by considering animal productivity, health, and welfare, while also supporting decision-making processes across the different research areas addressed by the project. This objective was successfully achieved, as each Operative Unit (OU) fully carried out the planned activities by conducting research on different PLF tools applicable to dairy farming. Specifically, the Operative Unit of the University of Bologna (UNIBO) achieved its objective of providing design and management criteria for optimizing environmental conditions in dairy cattle barns through the integration of heterogeneous monitoring systems, the development of integrated systems for monitoring environmental conditions, animal location and behaviour, the definition of protocols for data management and processing, and the modelling and simulation of livestock buildings. The Operative Unit of the University of Catania (UNICT) achieved its objective of developing an automated system for monitoring grazing dairy cows and cows within cow-calf production systems that is both economically sustainable for farmers and socially acceptable to local communities. The Operative Unit of the University of Florence (UNIFI) achieved its objective of developing and testing novel automated tools for monitoring social interactions among dairy cattle and exploring potential applications of the collected data throughout the production chain. The Operative Unit of the University of Milan (UNIMI) achieved its objective of evaluating the effectiveness of different techniques for monitoring and improving the growth of female calves from birth through weaning to replacement age, while assessing the sustainability of the investigated approaches in terms of their environmental, economic, and social implications for farms, as well as their investment and innovation potential.

The INDACAT project enabled each Operative Unit to advance research on the adoption of innovative technologies for monitoring different aspects of cattle production systems. However, as technologies continue to evolve rapidly, offering increasingly advanced capabilities and becoming more widely adopted on livestock farms, further research on the implementation of Precision Livestock Farming (PLF) technologies remains essential. From an environmental perspective, improving animal housing conditions, productivity, and resource-use efficiency is fundamental to reducing the environmental impact of the livestock sector. From a social perspective, enhancing animal welfare and improving working conditions for farm operators are key factors in encouraging generational renewal within the sector and increasing consumer awareness of livestock farming practices. Finally, from an economic perspective, farmers are willing to invest in new technologies only when they provide tangible opportunities for improvement and prove to be economically viable. Therefore, the development and refinement of these technologies must continue through research activities, enabling their subsequent practical implementation and wider adoption across the livestock sector.

D.D. del MUR n. 104 del 02/02/2022

Codice progetto MUR: 2022S4X9Y2

CUP: J53D23010420006

Coordinatore di progetto: Università di Milano

Ruolo UNIBO: RL

Scientific Officer: Patrizia Tassinari

Duration: 12/10/2023 - 12/10/2025

Research group: Patrizia Tassinari, Valda Rondelli.