The livestock sector is currently undergoing a profound revision of its production models to address the challenges posed by climate change and the growing demand for proteins. This work analyzes the integration between animal nutrition and sustainability, identifying the circularity of processes as the cornerstone for a new production paradigm in cattle. The analysis opens with overcoming the feed-food competition conflict, highlighting through the HeFCE indicator the capacity of ruminants to act as biosystems capable of valorizing fibrous biomasses non-edible for humans. In this context, the use of agro-industrial by-products is explored not only as a tool to reduce ration costs, but as a Life Cycle Assessment (LCA) strategy to eliminate the environmental footprint of supply chain residues. A central focus is dedicated to the mitigation of enteric methane and the reduction of nitrogen excretions; through the modulation of the ruminal microbiota and the adoption of local alternative diets to soybean meal in compliance with the EUDR regulation, it is demonstrated how to reduce the carbon footprint without compromising performance. Finally, the thesis explores the contribution of Precision Livestock Farming and predictive Machine Learning algorithms to monitor feed efficiency in real time. In conclusion, this strategy transforms the farm into a central node of the bioeconomy, ensuring the long-term resilience and competitiveness of the cattle sector.
Il settore zootecnico è attualmente impegnato in una profonda revisione dei propri modelli produttivi per rispondere alle sfide poste dal cambiamento climatico e dalla crescente domanda di proteine. Il presente lavoro analizza l'integrazione tra nutrizione animale e sostenibilità, individuando nella circolarità dei processi la chiave di volta per un nuovo paradigma produttivo nei bovini. L'analisi si apre con il superamento del conflitto feed-food competition, evidenziando tramite l'indicatore HeFCE la capacità dei ruminanti di agire come biosistemi in grado di valorizzare biomasse fibrose non edibili dall'uomo. In questo contesto, l'utilizzo di sottoprodotti agroindustriali viene approfondito non solo come strumento per abbattere i costi di razione, ma come strategia di Life Cycle Assessment (LCA) per azzerare l'impronta ambientale dei residui di filiera. Un focus centrale è dedicato alla mitigazione del metano enterico e alla riduzione delle escrezioni azotate; attraverso la modulazione del microbiota ruminale e l'adozione di diete locali alternative alla soia in linea con il regolamento EUDR, viene dimostrato come ridurre l'impatto carbonico senza compromettere le performance. Infine, la tesi esplora l'apporto del Precision Livestock Farming e di algoritmi predittivi di Machine Learning per monitorare l'efficienza alimentare in tempo reale. In conclusione, questa strategia trasforma la stalla in un nodo centrale della bioeconomia, garantendo la resilienza e la competitività del settore bovino nel lungo periodo.
Nutrizione Animale e Sostenibilità nei Bovini: la Circular Economy come strategia per ridurre l'impatto ambientale degli allevamenti
MALAFFO, ENRICO
2025/2026
Abstract
The livestock sector is currently undergoing a profound revision of its production models to address the challenges posed by climate change and the growing demand for proteins. This work analyzes the integration between animal nutrition and sustainability, identifying the circularity of processes as the cornerstone for a new production paradigm in cattle. The analysis opens with overcoming the feed-food competition conflict, highlighting through the HeFCE indicator the capacity of ruminants to act as biosystems capable of valorizing fibrous biomasses non-edible for humans. In this context, the use of agro-industrial by-products is explored not only as a tool to reduce ration costs, but as a Life Cycle Assessment (LCA) strategy to eliminate the environmental footprint of supply chain residues. A central focus is dedicated to the mitigation of enteric methane and the reduction of nitrogen excretions; through the modulation of the ruminal microbiota and the adoption of local alternative diets to soybean meal in compliance with the EUDR regulation, it is demonstrated how to reduce the carbon footprint without compromising performance. Finally, the thesis explores the contribution of Precision Livestock Farming and predictive Machine Learning algorithms to monitor feed efficiency in real time. In conclusion, this strategy transforms the farm into a central node of the bioeconomy, ensuring the long-term resilience and competitiveness of the cattle sector.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/110358