In this episode of The Poultry Nutrition Blackbelt Podcast, Emmanuel Nuamah, Research Assistant at Jeonbuk National University in South Korea, explains how meta-analysis combines data from multiple studies to deliver more reliable, evidence-based nutritional strategies for broilers and layers. He walks through the full meta-analysis process, from the PICO framework to bias screening, and discusses how machine learning is making the method even more dynamic and powerful. Listen now on all major platforms!

"Meta-analysis aggregates individual studies to reveal nutritional strategies that hold across real-world variability in commercial production."

Meet the guest: Emmanuel Nuamah is a Research Assistant at Jeonbuk National University in South Korea, specializing in broiler and swine nutrition, digestive physiology, and meta-analysis. His work focuses on building evidence-based nutritional strategies from pooled study data. He holds a B.Sc. in Agriculture and an M.Phil. in Animal Science from the University of Cape Coast, Ghana.

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What you'll learn:

• (00:00) Highlight
• (01:39) Introduction
• (03:14) Meta-analysis overview
• (05:25) Heterogeneity and context
• (06:45) PICO framework explained
• (08:22) Screening and bias removal
• (12:17) AI and machine learning role
• (13:41) Closing thoughts

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- Poultry Science Association

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