Egg-scanning AI may let hatcheries sort life, death and sex before chicks emerge
Researchers at the University of Illinois at Urbana-Champaign have developed an egg-scanning AI using hyperspectral imaging and machine learning to assess chicken egg viability, embryo sex, and mortality early in incubation. The technology could improve hatchery efficiency, reduce economic losses, and address animal welfare concerns by enabling early detection of non-viable embryos and male embryos. With up to 97% accuracy in predicting embryo mortality by day four, the system offers a non-invasive alternative to current methods.
- ▪The AI system uses hyperspectral imaging and machine learning to predict chick embryo mortality with up to 97% accuracy on day four of incubation.
- ▪Early detection of dead embryos can prevent biosecurity risks caused by bacterial growth in non-viable eggs.
- ▪Male chick culling, which affects around 6 billion chicks annually in the U.S., could be reduced through early sex determination of embryos.
- ▪Some European countries have banned male chick culling, increasing demand for non-invasive sex detection technologies in the poultry industry.
- ▪The research was published in British Poultry Science and Food Control, focusing on embryo mortality and sex determination, respectively.
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April 28, 2026 Egg-scanning AI may let hatcheries sort life, death and sex before chicks emerge by University of Illinois at Urbana-Champaign edited by Gaby Clark, reviewed by Robert Egan Gaby Clark Scientific Editor Meet our editorial team Behind our editorial process Robert Egan Associate Editor Meet our editorial team Behind our editorial process Editors' notes This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: fact-checked peer-reviewed publication trusted source proofread The GIST Add as preferred source A line-scan hyperspectral imaging system for sex determination in eggs: (a). Overall system setup for image acquisition, (b).
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