AI Technology Can Now Detect Spoiled Chicken in Seconds Using Smart Packaging

Scientists Develop AI-Powered System to Check Chicken Freshness in Real Time

A team of researchers has introduced a new artificial intelligence-based technology that can identify whether chicken is fresh or spoiled within seconds. The system combines smart food packaging with deep learning to provide a fast and non-destructive method for monitoring food quality.

The innovation uses special indicator films made from natural compounds extracted from red cabbage. These films react to gases produced during chicken spoilage and gradually change color over time. Fresh chicken keeps the film in a purplish-red shade, while spoiled chicken turns the indicator green due to bacterial activity and chemical changes inside the packaging.

Researchers paired this intelligent packaging with an advanced AI image detection model based on YOLOv8 technology. The deep learning system was trained to analyze color changes accurately and classify chicken freshness with impressive precision. According to the study, the model achieved extremely high detection accuracy under controlled testing conditions.

Experts believe this technology could help reduce massive food waste caused by inaccurate expiration dates and unnecessary disposal of edible products. Traditional labels only estimate freshness, while this system provides real-time quality monitoring based on the actual condition of the food.

The researchers also improved the system using attention-based AI mechanisms that helped the model recognize subtle color differences even under varying lighting conditions. The technology showed strong performance compared to older AI detection models and may also be useful in other industrial quality inspection systems.

This smart freshness detection method could eventually be integrated into supermarket packaging, food delivery systems, and mobile applications, allowing consumers and retailers to instantly check food quality before use. Scientists say future improvements in AI and smart sensors may expand the technology across the global food industry.

Although the findings are promising, researchers noted that the study is still in the preprint stage and has not yet been peer-reviewed. More testing under real market and supply-chain conditions will be needed before large-scale commercial adoption.

Source:

Research Square Preprint Study
https://www.researchsquare.com/article/rs-9194621/v1