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Test Before You Toss: Using ATP and AI to Assess Milk Freshness

CWSF · 2026 Agriculture, Fisheries & Food Gold Medal

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Overview

Food waste is a major issue in Canada, with much of it happening at the household level due to confusion about best-before dates. Many people throw away food that is still usable or rely on look, smell, and taste to judge quality, which are not always reliable. This project aims to reduce unnecessary food waste by developing a fast, simple method to assess milk quality at home. The system uses a handheld ATP bioluminescence test to measure bacterial activity in milk, producing a numerical result (RLU). Since bacterial growth is linked to decreasing quality, this data can be used to classify milk as fresh, nearing spoilage, or spoiled. A custom GPT model is integrated into a website where users input their test results and receive clear recommendations. By combining science, technology, and education, this project helps consumers make better decisions and reduce food waste.

Awards (3)

  • Challenge Award
  • Gold Medal
  • Selected for CWSF 2026

Competition history

  • CWSF 2026 Agriculture, Fisheries & Food

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Source: ProjectBoard / Youth Science Canada

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