Thomas Jones: Predicting Amino Acids In Real Time | Ep. 151
In this episode of The Poultry Nutrition Blackbelt Podcast, Thomas Jones, a PhD student at the University of Georgia’s Department of Poultry Science, presents research on using near-infrared reflectance spectroscopy (NIRS) to predict digestible amino acid content in soybean meal. By correlating rooster bioassay data with NIR spectra, the method enables rapid, real-time nutrient assessment at the feed mill level, helping nutritionists manage ingredient variability more effectively. Listen now on all major platforms!
"Lysine digestibility in soybean meal can range from 2.3 to 2.8%, and at 30% dietary inclusion, those small differences accumulate into significant performance impacts across the flock."
Meet the guest: Thomas Jones is a PhD student in Poultry Science at the University of Georgia, Athens, specializing in near-infrared reflectance spectroscopy for real-time nutrient analysis of poultry feed. His research focuses on correlating NIRS-based spectra with rooster bioassay data to predict digestible amino acid content in soybean meal, aiming to improve feed formulation accuracy and reduce analytical turnaround time at the feed mill level.
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What you'll learn:
- (00:00) Highlight
- (01:22) Introduction
- (02:15) Soybean meal variability
- (03:29) Bioassay limitations
- (05:35) Amino acid trends
- (07:05) NIRS throughput
- (09:09) Margin of error
- (16:01) Closing thoughts
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