Artificial intelligence for prediction of shelf-life of various food products: Recent advances and ongoing challenges

Accurate estimation of shelf-life is essential to maintain food safety, reduce wastage, and improve supply chain efficiency. Traditional methods such as microbial and chemical analysis, and sensory evaluation provide reproducible results but require time and labor and may not be suitable for real-time or high-throughput applications. The integration of artificial intelligence (AI) with advanced analysis techniques offers a suitable alternative for rapid, data-driven estimation of shelf-life in dynamic storage environments. The current review assesses the application of AI-based techniques such as machine learning (ML), deep learning (DL), and hybrid approaches in food product shelf life prediction. This study…

• SH
  Sheffield Hallam University