• Skip to primary navigation
  • Skip to main content

Aggie Collaborate

Texas A&M University

  • About Aggie Collaborate
  • Participate
  • Projects
  • Events
  • Contacts
  • Show Search
Hide Search

>Developing a System Dynamics Model for energy efficient and profitable beef production systems

Team Leader
Serin Pulikkottil
Texas A&M University
Animal Science
serinmarypulikkottil@tamu.edu

Project Type
Research

Who Can Join
Masters Students, Undergraduate Students

Project Description
This project brings together animal science and mathematical modeling to study livestock production systems as dynamic, interconnected systems. Livestock operations involve continuous interactions among animal biology, nutrition, management decisions, resource use, economics, and environmental outcomes, making them ideal candidates for System Dynamics (SD) modeling.

Animal science participants will contribute biological realism and domain expertise, helping define processes such as growth, feed intake, reproduction, health, and management practices. These processes will be translated into formal dynamic models through close collaboration with quantitative team members. The resulting model will allow the team to simulate realistic production scenarios, evaluate sustainability trade-offs, and explore how management decisions influence outcomes over time.

Math and quantitative participants will focus on model structure, feedback loops, equations, and dynamic behavior, while animal science participants ensure the assumptions, parameters, and outputs reflect real-world livestock systems. This paired-team approach allows each participant to deepen their own expertise while gaining exposure to a complementary discipline.

The project will produce a fully documented System Dynamics model, along with scenario and sensitivity analyses that generate publishable research outputs.

Team Needs
We are forming an interdisciplinary team to develop a System Dynamics (SD) model for complex livestock production systems. This project integrates mathematical modeling, data analysis, and animal science domain knowledge to build a decision-support tool for sustainability research.

Each participant will be paired with a complementary teammate (quantitative ↔ domain) to promote cross-disciplinary learning and real-world systems thinking.

1. Quantitative / Math Background (Modeling Track)

Ideal for students in mathematics, statistics, engineering, computer science, economics, or data science.

Looking for individuals with interest or experience in:

Systems thinking and complex systems

Differential equations, feedback loops, or dynamic modeling

Applied mathematics, statistics, or optimization

2. Animal Science / Life Sciences Background (Domain Track)

Ideal for students in animal science, veterinary science, biology, environmental science, agriculture, or related fields.

Looking for individuals with knowledge or interest in:

Livestock production systems (especially beef or grazing systems)

Nutrition, reproduction, health, genetics, or management

Sustainability metrics (emissions, productivity, welfare, economics)

Interpreting scientific literature and real-world management practices

Special Opportunities
Selected team members will have the opportunity to:

Co-author peer-reviewed journal publications resulting from the System Dynamics modeling work

Present research at the Student Research Week and other opportunities as they may arise, including poster and oral presentations

Gain experience in research writing, model documentation, and scientific communication

Build a strong interdisciplinary research portfolio suitable for graduate school, fellowships, and industry roles

Authorship and presentation opportunities will be merit-based and contribution-driven, following standard academic guidelines.

Categories: AI for Food Sustainability Systems, ResearchTags: Available

Footer

Texas A&M University  |  Web Accessibility  |  Site Policies  |  Site Support