Visible and Hyperspectral Imaging for Quality Assessment of Milk: Property Characterisation and Identification
Your phone's camera could soon spot bad milk before you smell it.
Deep Dive
A new AI study shows visible and hyperspectral imaging can assess milk quality non-destructively. Using a standard smartphone camera, machine learning models achieved 100% accuracy in distinguishing fresh milk from samples stored for 12 days and identifying antibiotic-treated milk. The system also perfectly predicted polyphenol content and antioxidant capacity. Hyperspectral imaging further classified individual fatty acids with over 95% accuracy, offering a rapid, cost-effective alternative to traditional lab analysis.
Why It Matters
This could revolutionize food safety by enabling instant, at-home quality checks for dairy and other perishable products.