Decision‐Centric Expert Systems for Quality Assurance and Food‐Safety‐Related Risk Management in Protected Tomato Production: Architectures, Data Fusion, and Validation Insights

ABSTRACT Protected tomato production is undergoing rapid digitalization, transforming greenhouses into cyber–physical systems that require intelligent decision support to strengthen quality assurance and address food safety‐related risks. Based on the PRISMA 2020 guidelines, this systematic review synthesizes 96 studies published between 2015 and 2025 to examine how expert systems are supporting the transition from automated environmental control to data‐driven management in protected tomato production. The reviewed literature is organized into four domains: agricultural robotics, artificial intelligence for perception and prediction, Internet of Things (IoT) infrastructures, and integrated fertigation systems. Despite substantial progress, current systems still face fragmented data silos, limited adaptability in unstructured environments, insufficient external validation, and limited evaluation of postharvest quality outcomes. This review highlights the need for stronger validation frameworks, improved interoperability, explainable artificial intelligence (XAI), and more effectively coordinated cyber–physical architectures to support scalable protected tomato production with stronger quality and safety assurance.