LC–MS/MS-based metabolomics coupled with machine learning for screening candidate biomarkers in bacon

Key Points

• Candidate biomarkers for bacon have been identified using machine learning techniques, emphasizing the role of metabolomics.
• The analysis found distinct biomarker patterns by integrating mass spectrometry data and machine learning algorithms.
• Observational analysis showed significant results, indicating potential implications for food safety standards and quality control.
• Potential for wider applications in food science, though further studies are needed to confirm the findings.