11^th International Conference on Food Chemistry & Technology

The use of plastic packaging in the food industry is under increasing scrutiny due to its environmental impact. With production having tripled over the last 30 years, almost 400 million metric tons of plastics are produced annually, accounting for 4.5% of global greenhouse emissions. Over 99% of these plastics are derived from fossil-based polymers, which persist in the environment for hundreds of years, posing significant ecological risks. The food and beverage sector is the largest consumer of single-use plastic packaging, yet transitioning away from plastic entirely is impractical due to its crucial role in food preservation, safety and hygiene. A circular economic approach, wherein plastic packaging is reused multiple times before closed-loop recycling, offers a promising strategy for mitigating environmental impacts within food provision. However, several technical challenges hinder widespread implementation, including the need for effective cleaning validation, prevention of cross-contamination, and assessment of packaging integrity to ensure safety, suitability for automated systems and consumer acceptance. Currently, no commercially available solutions comprehensively assess the suitability of every pack for reuse. This work explores the application of ultraviolet induced fluorescence imaging (UVIFI) combined with deep learning (DL) models to automate the detection of residual food contamination and assess packaging condition. Utilizing UVIFI of fluorophores within foodstuffs and polymers enables the real-time detection of residual fouling across the full food contact area and analysis of pack integrity. The developed system enables automated defect classification, facilitating reliable verification of packaging suitability for reuse. Results demonstrate the potential of integrating UVIFI and DL for accurate defect identification. Such a technological solution supports scalable circular economy reuse systems and could underpin environmental impact limitation in the food sector.

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