Next-generation intelligent prepared aquatic dishes: research progress in digital heat control and quality evaluation empowered by industry 4.0.

Aquatic prepared dishes require reproducible doneness control during industrial stir-frying and reheating, yet their thermally labile proteins, mobile water fractions, and oxidation-prone unsaturated lipids make product quality highly dependent on thermal history. This review systematically examines heat-induced quality evolution in fish, shrimp, surimi, and other aquatic food matrices, and evaluates aquatic-specific and transferable Industry 4.0 technologies for digital doneness control and quality evaluation. The reviewed evidence indicates that doneness is not a single endpoint temperature or fixed heating time, but a dynamic quality state shaped by protein denaturation, moisture redistribution, lipid oxidation, color development, and volatile release. Accordingly, differential scanning calorimetry (DSC) denaturation descriptors, low-field nuclear magnetic resonance (LF-NMR)-derived T₂ relaxation features, L*/a*/b* trajectories, texture indices, oxidation markers, and volatile fingerprints can be used as model inputs, constraints, labels, or control thresholds. However, current research still lacks aquatic-specific datasets, unified doneness labels, real-time links between mechanistic indicators and control actions, robust validation under raw-material heterogeneity, and reliable sensing under sauce coverage, steam interference, and oil-fume exposure during stir-frying. To address these gaps, this review proposes a mechanism-informed closed-loop framework integrating raw-material state recognition, multimodal sensing, digital-twin prediction, artificial intelligence (AI)-based heating-trajectory regulation, flexible execution, and quality verification. Future breakthroughs should prioritize standardized datasets, cross-batch and pilot-scale validation, interpretable control models, online-offline sensor calibration, sustainability indicators, and resilience-oriented industrial deployment. This framework supports the transition from experience-based aquatic stir-frying to scalable, auditable, and quality-oriented intelligent manufacturing.