Metabolomics-Driven Insights into Rice Wine Fermentation: From Descriptive Profiling to Intelligent Process Control

Rice wine fermentation involves complex biochemical dynamics that challenge traditional empirical control, highlighting the need for precise analytical characterization. This narrative review synthesizes the technological evolution of metabolomics from a descriptive tool to a driver of intelligent biomanufacturing. The progression from first-generation compositional profiling to third-generation strategies integrating high-resolution mass spectrometry, real-time sensing, multi-omics approaches, and artificial intelligence is delineated. This evolution has shifted research focus from static component cataloging to dynamic pathway elucidation, enabling deeper interpretation of flavor biosynthesis, functional metabolite formation, and accumulation of safety-related metabolites. Furthermore, this review critically analyzes how multi-omics integration reveals microbiome-metabolite interactions and provides mechanistic targets for quality regulation. Despite these advances, a gap remains between laboratory-scale analytical capabilities and industrial implementation. Key translational bottlenecks are identified, and a future roadmap toward AI-driven digital twin systems and real-time adaptive control is proposed. This framework positions metabolomics not merely as an analytical technique, but as a key foundation of next-generation smart fermentation strategies.