Metabolomic profiling and functional regulation of rabbit meat: from pre-harvest to post-mortem changes

Metabolomics has emerged as a transformative analytical platform for elucidating the biochemical mechanisms that underpin meat quality, nutritional value, and functional attributes. Rabbit meat is increasingly recognized as a viable alternative to conventional meats due to its lean composition, high-quality protein, and favorable lipid profile. Comparative evidence indicates that rabbit meat typically exhibits a polyunsaturated-to-saturated fatty acid (PUFA/SFA) ratio ranging from approximately 0.60 to >1.0, depending on breed and muscle type, values that consistently exceed those reported for beef and pork and are comparable to or higher than poultry, underscoring its nutritional advantage. Despite substantial advances, the practical deployment of metabolomics in rabbit meat research remains constrained by critical gaps, including the lack of standardized sample preparation and metabolite identification frameworks, incomplete metabolome coverage across analytical platforms, limited validation and transferability of candidate biomarkers, insufficient integration with genomics, transcriptomics, and proteomics, and the predominance of destructive, low-throughput methodologies that limit real-time industrial application. The unique contribution of this review lies in its systems-level integration of metabolomic drivers across the entire production continuum, from pre-harvest biological regulation (genotype, nutrition, and management) to post-mortem biochemical transformations and storage dynamics, coupled with a translation-oriented framework that bridges mechanistic discovery with emerging non-invasive technologies and industrial quality control strategies. By consolidating fragmented evidence into a coherent mechanistic and applied roadmap, this review provides strategic guidance for advancing reproducibility, predictive capability, and scalability of metabolomics in rabbit meat systems, thereby supporting the development of data-driven interventions to enhance meat quality, processing efficiency, and functional value.