Smart Process Monitoring and Closed-Loop Control for Resource-Efficient Food Processing

The food processing sector is increasingly moving toward intelligent and resource-efficient processing systems capable of delivering safe, high-quality foods with reduced energy, water, material, and processing requirements. Emerging thermal, non-thermal, and hybrid technologies offer considerable opportunities for process intensification and quality preservation; however, their successful implementation requires accurate real-time monitoring and reliable closed-loop control. Recent advances in smart sensing, process analytical technologies, and feedback control systems, increasingly supported by process modeling and data-driven methods such as artificial intelligence and machine learning, are providing new opportunities for real-time process assessment and in-process decision-making. Integrating these sensing and control approaches with food processing technologies (traditional thermal, advanced thermal, and nonthermal) can improve process efficiency, reproducibility, safety, quality, and scalability. Such integration is particularly important for translating laboratory-scale innovations into reliable pilot- and industrial-scale processes while addressing increasing demands for sustainable and resource-efficient food production.This Research Topic aims to highlight advances in real-time monitoring and closed-loop control strategies for resource-efficient food processing. The Topic will bring together interdisciplinary research integrating food process engineering with smart sensing and control technologies to improve the performance, reliability, sustainability, and scalability of food processing systems. Particular emphasis will be placed on smart sensors, process analytical technologies, and feedback control systems for process monitoring and control, with process modeling, artificial intelligence, and machine learning welcomed where they directly support sensing accuracy or control performance rather than as a standalone focus. Contributions addressing traditional thermal processing, advanced thermal technologies (e.g., microwave, ohmic heating), nonthermal technologies (e.g., high pressure, pulsed electric fields, UV, pulsed light), and hybrid processing technologies are encouraged, particularly where real-time monitoring and control approaches are used to reduce energy and resource consumption while maintaining food safety, nutritional value, physicochemical properties, sensory quality, and shelf life. The Topic will also address process intensification, real-time quality and safety monitoring, process validation, scale-up, and the transition from laboratory research to pilot- and industrial-scale implementation. Overall, the Research Topic seeks to advance engineering approaches that enable food processing systems to become more precise, adaptive, resource-efficient, and practically scalable.This Research Topic welcomes original research articles, reviews, and perspectives addressing real-time monitoring and closed-loop control of food processing systems. Topics of interest include, but are not limited to:o Smart monitoring and real-time control of food processing operationso Smart sensors, IoT-enabled monitoring, and process analytical technologieso Feedback and closed-loop control strategies for food processing operationso Traditional thermal processing technologieso Advanced thermal technologies (e.g., microwave, ohmic heating, etc.)o Nonthermal technologies (e.g., high pressure, pulsed electric fields, UV, pulsed light, cold plasma, ultrasound, etc.)o Hybrid food processing technologies and related emerging technologieso Real-time control of drying, heating, cooling, concentration, extraction, preservation, and other unit operationso Process intensification and reduction of energy, water, and material consumptiono Sustainable and resource-efficient process designo Monitoring and control of microbial safety, quality, and shelf-life attributeso Process validation, predictive processing, and quality assuranceo Scale-up, pilot-scale studies, industrial implementation, and technology transfero Data-driven and AI/ML-supported methods, where applied in direct service of sensing, monitoring, or control performanceManuscripts should demonstrate clear engineering significance, methodological rigor, and a meaningful contribution to process performance, resource efficiency, food safety, quality, or scalability. Studies integrating experimental processing with sensing, monitoring, or control are particularly encouraged. Topic editors: Anbarasan Rajan, Kaavya Rathnakumar, Anto Pradeep Raja Charles Source: https://www.frontiersin.org/research-topics/86188/smart-process-monitoring-and-closed-loop-control-for-resource-efficient-food-processing