Workshops & Symposia
Nutrition modeling in the R language is an important component of nutritional research. In the Nutrition Models Workshop, you will learn the modeling approaches required to construct, parameterize, and evaluate a model.
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Unassigned organic matter in feeds. Fred Owens, Oklahoma State University, Stillwater, OK. |
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Inconsistencies in fiber analysis affecting feed analysis databases. David R. Mertens, Mertens Innovation & Research LLC, Belleville, WI. |
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Protein analysis methodology. Glen A. Broderick, formerly US Dairy Forage Research Center, USDA-ARS, Madison, WI. |
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Success and continuing challenges in analyzing nonfiber carbohydrates. Mary Beth Hall, The Cows Are Always Right LLC (formerly US Dairy Forage Research Center, USDA-ARS, Madison, WI). |
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Assessing accuracy and validity of assays from commercial feed analysis laboratories. Nicole Schlau, Dairyland Laboratories, Arcadia, WI. |
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Development of an evergreen, interactive, and consolidated dataset of feedstuff nutrient composition. Ryan N. Dilger, University of Illinois at Urbana-Champaign. |
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Introduction. Luis Tedeschi, Texas A&M University. Profile |
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Precision livestock farming: Harnessing artificial intelligence for animal management. Isabella Condotta, University of Illinois at Urbana-Champaign. Profile |
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Combining dynamic models with deep learning through time series analysis. Hossein Moradi Rekabdarkolaee South Dakota State University. Profile |
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Applying system dynamics to develop “flight simulators” for sustainable animal production. Hector Menendez, III, South Dakota State University. Profile |
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Environmental evaluation of feeding strategies with agent-based modeling and life cycle assessment: from theory to practice. Florence Garcia-Launay, INRAE UMR PEGASE. Profile |
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Introduction to developing Python computational pipelines for predictive machine learning modeling of livestock data. Dan Tulpan, University of Guelph. Profile |
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Introduction. Luis Tedeschi, Texas A&M University. Profile |
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Advantages, difficulties, and pitfalls of processing and combining different types of real-time data. Tami Brown-Brandl, University of Nebraska-Lincoln. Profile |
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Satellite-based decision support tools to assist grazing cattle production. Marcia Fernandes, São Paulo State University. Profile |
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Overview of poultry modeling evolution. Edgar Oviedo-Rondon, North Carolina State University. Profile |
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Building an Agent-Based Model in AnyLogic. Wade McDonald, University of Saskatchewan. Profile |
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The role of system dynamics modeling for sustainable livestock production. Alberto Atzori, University of Sassari. Profile |
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| Building digital twins for precision livestock farming: Data analytics and big data challenges. Jian Tao, Texas A&M University. Profile |
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Introduction. Luis Tedeschi, Texas A&M University. Profile |
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The Power of Theoretical and Practical Identifiability Analysis for Modeling (micro-) Biological Processes. Rafael Muñoz-Tamayo, INRAE-AgroParisTech, University Paris-Saclay. Profile |
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Automation, Machine Learning and Computer Vision as Decision Support. Scott McClain, SAS Institute. Profile |
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Buidling Models for Animal Production and Management with System Dynamics Modeling: A Basic Introduction to System Dynamics Modeling. Benjamin Turner, Texas A&M University-Kingsville. Profile |
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Hands-on: Agent-Based Modeling in Agriculture. Karun Kaniyamattam, Texas A&M University. Profile |
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Hands-on: Making Sense of Big Data, Machine Learning, and Modeling. Jameson Brennan, South Dakota State University. Profile |
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Introduction. Luis Tedeschi, Texas A&M University. Profile |
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Opportunities and Limitations of Modeling and Data Analytics for Precision Livestock Farming. Aline Remus, Agriculture and Agri-Food Canada. Profile |
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Application of Precision Sensor Technologies, Real-time Data Analytics, and Dynamic Models on Extensive Western Rangeland Grazing Systems. Hector M. Menendez, III, South Dakota State University. Profile |
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Mapping Resilience Indicators and Measuring Emotions of Farm Animals Using Sensor Data. Suresh Neethirajan, Wageningen University & Research. Profile |
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The Adoption of AI in the Core Scientific Cycle of Feed Research. Marc Jacobs, Trouw Nutrition. Profile |
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Integrating Mechanistic Models with AI for Precision Feeding of Sows. Charlotte Gaillard, PEGASE, INRAE, Institut Agro, France. Profile |
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EnROADS: Overview of Climate Change Modeling. Charles Jones, Climate Interactive. Profile |
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Statistical Graphics and Interactive Visualization in Animal Science. Gota Morota, Virginia Polytechnic Institute and State University. Profile |
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A Brief Overview, Comparison and Practical Applications of Machine Learning Models. Dan Tulpan, University of Guelph. Profile |
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Tutorial on R. Tim Hackmann, University of California, Davis. Profile |
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Parameter estimation: Lecture and exercises. Kristan Reed, Cornell University. Profile |
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Cross-validation and bootstrapping: Lecture and exercises. Ranga Appuhamy, Iowa State University. Profile |
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Automated model selection: Lecture and exercises. Veridiana Daley, Land O'Lakes, Davis. Profile |
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Molly and other dynamic models: Lecture and exercises. Heidi Rossow, University of California, Davis. Profile |
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Introduction. Luis Tedeschi, Texas A&M University. Profile |
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Building models using system dynamics methodology: applications to animal science. Emma C. Stephens, Agriculture and Agri-Food Canada. Profile |
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Modelling digestion kinetics in pigs. Walter Gerrits, Wageningen University & Research. Profile |
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A brief overview, comparison and practical applications of machine learning models (theoretical background, demos, instructions + hands-on examples). Dan Tulpan, University of Guelph. Profile |
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Statistical graphics and interactive visualization in animal science. Gota Morota, Virginia Polytechnic Institute and State University. Profile |
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Tutorial on R. Veridiana Daley, Land O'Lakes. |
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Model construction. Timothy Hackmann, University of California, Davis. |
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Evaluating model predictions. Henk van Lingen, University of California, Davis. |
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Meta-analysis. Veridiana Daley, Land O'Lakes, Davis. |
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Building a nutrient requirement model. Mark Hanigan, Virginia Tech. |
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Linear Models and Meta-Regression (Theoretical background including instructions for practical, followed by hands-on examples) Dr. Kristan Reed Cornell University, USA |
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Mechanistic Models (Theoretical background including instructions for practical, followed by hands-on examples). Dr. Mark Hanigan, Virginia Tech |
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Install R and RStudio - NANP and Virginia Tech Dr. VL Daley and Members of Dr. Hanigan's Lab (Xinbei, Alvaro, Leticia, Jacquelyn, Alexis) |
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ASAS-NANP Symposium Introduction |
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Introduction to mathematical models, Mark D. Hanigan Virginia Tech, Virginia, USA |
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Building Models for Animal Production and Management with System Dynamics Modeling. Benjamin L. Turner, Texas A&M University-Kingsville |
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Introduction to R and R Scripting Robin R. White, Department of Animal and Poultry Sciences, Virginia Tech. |
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Assessing the predictive adequacy of simple and complex mathematical models Luis O. Tedeschi, Texas A&M University. |
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Overview and Case Studies of Cutting Edge Artificial Intelligence Techniques. Hector Menendez, Texas A&M University. |
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Welcoming remarks. John McNamara, Washington State University. |
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Tutorial on R.Timothy Hackmann, University of California, Davis. |
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Estimation of Parameter Values: lecture. Mark Hanigan, Virginia Tech. |
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Lesson 1: Estimation of Parameter Values: exercises. Mark Hanigan, Virginia Tech. |
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Bootstrap and Cross-Validation: lecture. Ranga Appuhamy, Iowa State University Ames. |
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Lesson 2: Bootstrap and Cross-Validation: exercises. Ranga Appuhamy, Iowa State University Ames. |
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Automated Model Selection: lecture. Veridiana L. Daley, University of Kentucky. |
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Lesson 3: Automated Model Selection: exercises. Veridiana L. Daley, University of Kentucky. |
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Molly and other dynamic models: lecture. Heidi Rossow, University of California, Davis. |
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Lesson 4: Molly and other dynamic models: exercises. Heidi Rossow, University of California, Davis. |
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Relevance and Collaboration with the National Research Council. Merlin D. Lindemann, University of Kentucky. The National Animal Nutrition Program (NANP). Profile |
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Food and Agriculture Cyberinformatics and Tools. Charlotte Kirk Baer. National Program Leader. National Institute of Food and Agriculture US Department of Agriculture. Profile |
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The evolution of mathematical models for animal nutrition: what to expect next? Luis Tedeschi, Texas A&M University. Profile |
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Combining simplicity and complexity: creating user-applications from mechanistic nutritional models. Jaap van Milgen, INRA. Profile |
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Modeling the impact of climate change on whole farm systems. Andrew D. Moore, Digiscape Future Science Platform, CSIRO. Profile |
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Decision support for foot-and-mouth disease emergency preparedness: the use of computer modeling and visual analytical tools to evaluate control strategies. Lindsey Holmstrom, USDA-NAHMS. Profile |
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Modeling complex problems with system dynamics: Applications in Animal Agriculture. Charles Nicholson, College of Agriculture and Life Sciences. Profile |
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Innovative ways to see data. John C. Hart, University of Illinois at Urbana-Champaign. Profile |
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1) Download and Install R 2) Download and Install R Studio (after installing the R) 3) Tutorial: Install R packages In RStudio, you will need to install several packages (caret, deSolve, epiR, ggplot2, lmerTest, lme4, MuMIn, plyr, reshape2). This tutorial explains how to install the packages (as well as how to install R and RStudio). 4) Download the R script and install the packages |
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Introduction and model construction (Part I and II). T. J. Hackmann, M. D. Hanigan, V. L. Daley. |
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Model evaluation (Part I and II). E. Kebreab. |
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Meta-analysis (Part I). R. R. White. |
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Opportunities for federal funding of modeling research. S. I. Smith. |
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Welcoming remarks |
Presentation |
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Purposes and types of models. M. D. Hanigan. |
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Dynamic deterministic models. T. Hackmann. |
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Estimation of parameter values in nutrition models. L. Moraes. |
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Model evaluation. E. Kebreab. |
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Example models for ruminant digestion and metabolism. H. A. Rossow. |
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Meta-regression analysis of animal nutrition literature. R. R. White. |