Dr. Jennifer Ellis, an Associate Professor of Animal Systems Modeling at the University of Guelph, dives into how machine learning can revolutionize feed mill systems and pellet quality. She discusses the balance between efficiency and quality in poultry feed production, highlighting innovative data-driven strategies. Dr. Ellis also clarifies the roles of AI and machine learning, exploring their impact on enhancing feed performance. Get ready to learn how these groundbreaking approaches are shaping the future of poultry production!
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question_answer ANECDOTE
Botched Experiment Sparks Idea
Dr. Ellis's feed manufacturing trials were confounded by unexpected poor pellet quality.
This sparked her interest in using machine learning to predict and understand pellet quality outcomes.
insights INSIGHT
Pellet Quality's Impact
Pellet quality significantly impacts animal performance, especially in monogastrics.
Poor quality and high fines can reduce feed conversion and create nutrient delivery inconsistencies.
insights INSIGHT
Machine Learning Defined
Machine learning, a subfield of AI, trains algorithms on data to predict outcomes with new data.
The rise of big data in agriculture allows for better analysis using these existing algorithms.
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In this episode of The Poultry Podcast Show, Dr. Jennifer Ellis from the University of Guelph talks about how machine learning can improve feed mill systems and pellet quality. She shares practical insights on boosting efficiency and consistency in the poultry industry using cutting-edge, data-driven strategies. Discover how these innovations are shaping the future of poultry production and helping to ensure top-notch animal performance. Don’t wait—catch the episode now on your favorite podcast platform!
"Machine learning in agriculture bridges complex data sets with actionable insights for feed mill optimization."
Meet the guest:
Dr. Jennifer Ellis serves as an Associate Professor of Animal Systems Modeling at the University of Guelph, where she also earned her MSc and PhD in mathematical modeling. Her research focuses on mechanistic modeling, machine learning, and system optimization, contributing to groundbreaking insights into animal production systems. With a unique blend of academic and industry expertise, Dr. Ellis brings forward-thinking approaches to improving feed mill systems.
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