Daniele Torreggiani
Papers
2
Total Citations
31
H-Index
2
About
Daniele Torreggiani’s research sits at the intersection of precision livestock farming, animal welfare, and agricultural data science. His work focuses on developing data-driven models to improve herd management and early detection of stress in dairy cattle. In his highly cited 2018 paper, Torreggiani introduced a cluster-graph model for characterising herd behaviour in dairy farms using automatic milking systems—a novel approach that enables farmers to detect subtle changes in production and welfare patterns. This work has garnered 23 citations and remains foundational for researchers applying network analysis to livestock monitoring. More recently, his 2024 DAIRY CHAOS project tackles the pressing issue of heat stress in intensive dairy systems, proposing a framework for early identification of affected cows through irregular production signals. By linking facility design, management strategies, and real-time data, Torreggiani’s contributions directly support the development of more resilient, welfare-conscious farming systems. His work is especially valuable for students and researchers interested in how computational modelling can transform traditional animal agriculture into a smarter, more responsive industry.
Research Focus
Key Achievements
Top Papers
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