Selected Recent Modeling Papers

A curated set of publications spanning mechanistic models, predictive analytics, sensor-driven decision support, and emerging computational paradigms.

This collection of papers documents a coherent, multi-year intellectual trajectory that traces the evolution of mathematical modeling in animal nutrition from classical mechanistic frameworks to modern, data-driven, and systems-level approaches. Collectively, the works articulate how advances in data analytics, sensor technologies, artificial intelligence, and, more recently, large language models and quantum computing, are reshaping decision support in livestock systems. The series integrates methodological foundations (model classifications, paradigms, and synthetic data generation), applied domains (ruminant nutrition, methane mitigation, precision livestock farming, and ecosystem services), and capacity building (training frameworks and pedagogical models for new researchers). Together, these papers provide both a conceptual roadmap and practical evidence for leveraging modeling, AI, and systems thinking to support sustainable, resilient, and societally relevant animal production systems.

PDF links open documents Journal/DOI included in each citation

Papers

Click a citation to open the PDF.