Sirish Subash, a student at The Gwinnett School of Mathematics, Science, and Technology (GSMST) in Snellville, Georgia, earned the title of America’s Top Young Scientist in 2024 and a $25,000 cash prize at the 3M Young Scientist Challenge. Driven by a desire to build products that make the world a better place, he invented PestiSCAND, a handheld, AI-powered device designed to detect pesticide residue on fresh produce.
Subash’s motivation grew from concerns about the cumulative health risks of long-term exposure to agricultural pesticides, which can linger on food even after standard rinsing.
How PestiSCAND Works
PestiSCAND works using spectrophotometry, shining light across various wavelengths onto the surface of fruits or vegetables and measuring how light reflects back. Custom machine learning algorithms then analyze these unique optical patterns to identify the distinct spectral signatures of chemical residues without swabbing, cutting, or damaging the produce.
Subash emphasizes that PestiSCAND is designed to complement, not replace, standard washing practices. While washing removes loose dirt and some surface chemicals, pesticides can remain trapped in outer skin layers or natural wax coatings. PestiSCAND gives consumers quick data on whether produce remains contaminated after rinsing, helping them decide whether to wash further, peel, or source differently.
Introducing Portability
Turning an ambitious concept into a practical tool required significant design iterations:
- Initial Setup: Early testing relied on a larger setup that functioned in fixed conditions.
- Handheld Device: Subash redesigned the tool into a portable, battery-powered form factor with integrated lighting, on-board sensing, and bluetooth connectivity.
By shrinking the hardware, he turned a specialized laboratory technique into a non-invasive appliance suitable for everyday home kitchens and grocery store aisles. In trials across thousands of samples, PestiSCAND achieved over 85% accuracy on items like spinach and tomatoes.
The Future Roadmap
He isn’t stopping at this version. Subash plans to improve the sensor for greater accuracy, train the AI model on more samples, and eventually transform PestiSCAND into a smartphone accessory. He aims for a target retail cost around $20, making real-time produce scanning accessible to everyday households.
