The PhD project aims to develop and validate advanced models to describe nutrient digestion and utilization in dairy cattle, with a specific focus on Italian hay-based feeding systems. Starting from a critical review of existing models, the project integrates experimental data, mathematical modeling, and simulation approaches to accurately represent ruminal degradation, total digestion, and nutrient efficiency. Particular attention is given to production systems linked to Parmigiano Reggiano, characterized by the absence of silages and high variability in forage quality. The creation of a comprehensive database will improve the predictive capacity of models for intake, production, milk composition, and emissions. The final goal is to optimize feeding efficiency, enhance productive and qualitative performance, and reduce the environmental impact of dairy farming systems.
- A critical review of the literature on models of ruminal digestion, intermediary metabolism, and energy and protein balances in dairy cattle, with the aim of identifying existing models, analyzing their limitations, and highlighting potential areas for improvement. The main reference models include the Cornell and NASEM systems (developed in North America on silage-based diets) and INRAE and NorFor (developed in Northern Europe on grass-based diets). However, Italian hay-based diets, typical of production systems regulated by the Parmigiano Reggiano specifications, are not adequately represented in existing rationing programs.
- Specific training through advanced courses in statistics, modeling, data mining, and machine learning to develop the methodological and computational skills required for subsequent phases of the project.
- Applied training in data management, including activities related to the creation, organization, and harmonization of datasets from previous studies, in order to build a coherent and usable database for the development of predictive models.