Evaluation of Novel Nutritional Strategies for Livestock Using Metabolic or Mathematical Method
A special issue of Veterinary Sciences (ISSN 2306-7381). This special issue belongs to the section "Nutritional and Metabolic Diseases in Veterinary Medicine".
Deadline for manuscript submissions: 19 March 2026 | Viewed by 28
Special Issue Editors
Interests: phytogenic additives; meta-analysis; animal nutrition; animal metabolism
Special Issue Information
Dear Colleagues,
Traditional metabolic studies have been a valuable tool in animal nutrition for several decades. However, several currently available mathematical and laboratory methodologies can complement or combine traditional animal nutrition studies to gain deeper insights into animal metabolism. For example, meta-analyses and mathematical simulation models represent transformative methodologies in livestock nutrition research, offering unprecedented precision in nutritional evaluation and predictive insight into animal metabolic responses. These analytical frameworks are crucial in optimizing dietary formulations, enhancing animal productivity, and promoting sustainable livestock systems. Despite their potential, current nutritional modeling encounters significant limitations, notably in the incomplete integration of complex metabolic interactions, heterogeneous data quality across studies, and insufficient validation against diverse physiological states and environmental conditions. These gaps underscore the need for methodological refinement and broader interdisciplinary integration.
Emerging trends, particularly the advent of computational metabolomics, artificial intelligence-driven analytics, and advanced stochastic modeling, promise to overcome existing constraints. Integrating machine learning algorithms with dynamic metabolic simulations can substantially improve predictive accuracy, enabling more robust nutritional strategies. Concurrently, advancements in multi-omics technologies and systems biology approaches facilitate deeper insights into the interactions between dietary interventions and metabolic pathways, emphasizing the importance of metabolic flexibility and resilience in livestock. Such multidisciplinary endeavors promise significant advancements in precision livestock farming, ultimately leading to improved animal health, productivity, and environmental sustainability.
Innovative lines of research for this Special Issue include, but are not limited to, the following:
- Traditional meta-analyses or metabolic studies on novel additives or ingredients for livestock;
- The assessment of individual nutritional requirements through predictive analysis, simulations, or computational metabolomics;
- The development of hybrid models that combine empirical meta-analyses with mechanistic simulations;
- The use of machine and deep learning methods for real-time nutritional management;
- The application of blockchain technologies to standardize the collection and validation of nutritional data.
Dr. José Felipe Orzuna-Orzuna
Dr. Lorenzo Danilo Granados-Rivera
Guest Editors
Manuscript Submission Information
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Keywords
- meta-analysis
- mathematical simulation modeling
- computational metabolomics
- machine learning
- predictive analytics
- sheep and goats
- beef and dairy cattle
- poultry, rabbits and swine
- feed additives
- animal metabolism
- metabolomic
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