Electronic Nose Boosts Food Safety and Livestock Monitoring

Researchers at the University of California, Berkeley have created an electronic nose that uses 16 gas sensors combined with machine‑learning algorithms to identify the scent signatures of spoiled food and common allergens. Early tests show the device can detect spoilage earlier and more accurately than human noses. The work, led by PhD student Carla Bassil under senior author Ali Javey, was published in Science Advances in June.

Australian ag‑tech startup Agscent, founded by Bronwyn Darlington, raised US$5 million to add AI capabilities to its “digital dog’s nose” that analyzes cattle breath. The system can determine pregnancy as early as 18 days after insemination, detect illness and measure methane emissions to improve feed efficiency. Agscent is conducting large‑scale validation trials with Dairy Farmers of America in the United States, building on sensor technology originally developed for NASA’s astronaut monitoring.