Exploring Trends and Future Developments in the Application of Artificial Intelligence in Food Processing and Preservation

Abstract Artificial intelligence (AI) is transforming food processing and preservation, offering significant opportunities to improve efficiency, safety, quality, and sustainability. This systematic review examines the application of AI technologies in this field, with particular emphasis on machine learning, deep learning, computer vision, and robotics. Using a PRISMA-based approach, literature published between 2015 and 2025 was analysed to identify major research trends, leading contributors, and emerging thematic areas. The review shows that AI has been widely applied in quality control and inspection, process optimisation, shelf-life prediction, intelligent packaging, predictive maintenance, and cold-chain monitoring. AI-driven systems have demonstrated strong capability in analysing complex datasets, detecting abnormalities, modelling food processes, improving decision-making, and enhancing food safety across the value chain. Bibliometric and thematic evidence further indicates that the field is rapidly expanding and increasingly interdisciplinary. However, most reported applications remain at laboratory or pilot scale, with limited industrial-scale implementation. Key barriers include data quality, model robustness, real-time integration, and limited cross-process deployment. Ultimately, these challenges underscore the need for ongoing research and development in AI technologies to realise their promise within the food business further. Future research directions encompass the amalgamation of AI with biotechnology, advancing more resilient and interpretable AI models, and formulating ethical standards for the appropriate application of AI in food processing and preservation. Therefore, this article serves as a significant resource for scholars, practitioners, and industry experts seeking to leverage the full capabilities of AI to elevate the food processing and preservation industry.