Innovative Non-Thermal and Advanced Processing Technologies for Optimizing Nutrient Retention and Extending Food Shelf Life: Integration of Machine Learning for Process Optimization

ABSTRACT: Conventional thermal processing methods such as drying, salting, fermentation, pasteurization, and sterilization remain the backbone of food processing and preservation. However, heat-induced losses of vitamins, pigments, bioactive compounds, and texture quality often compel manufacturers to explore alternative approaches to satisfy evolving consumer demands. In response to the increasing preference for minimally processed foods that retain nutritional quality and fresh-like characteristics, researchers and industry stakeholders have turned to innovative non-thermal and advanced processing technologies. This comprehensive review evaluates the current landscape of non-thermal technologies, including high hydrostatic pressure (HHP), pulsed electric field (PEF), ultrasonication (US), cold plasma (CP), UV irradiation (UVC), and ozonation, that effectively inactivate spoilage and pathogenic microorganisms while operating at ambient or modest temperatures. Additionally, recent advances in artificial intelligence (AI) and machine learning (ML) optimization for these technologies are explored, highlighting their potential to enhance process efficiency, predict microbial inactivation kinetics, and optimize nutritional retention. These methods preserve sensory qualities, improve techno-functional properties, support better digestibility and oxidative stability, and significantly extend shelf life across various food matrices with minimal thermal degradation. Keywords: Food processing, non-thermal technologies, hydrostatic pressure, ultrasonication, ozonation, oxidative stability, machine learning, artificial intelligence, process optimization