METABOLOMICS: Applications for Food Safety and Quality Control

Significance of the Topic

Food metabolomics employs comprehensive analytical techniques to profile small molecules that arise during biological processes. In the food industry, it strengthens quality control, safety assurance, functional food development and origin authentication. By capturing detailed metabolite fingerprints, it complements sensory evaluation and enhances traceability, helping to safeguard consumer health and maintain product value.

Objectives and Study Overview

This summary presents three illustrative applications of food metabolomics using Shimadzu’s advanced platforms:

• Analysis of aroma compounds and metabolites in different sake types
• Determination of geographical origin of agricultural produce (asparagus)
• Evaluation of deterioration characteristics in alcoholic beverages during accelerated aging

Methodology and Instrumentation

Each application combined targeted extraction or derivatization with high-resolution separation and tandem mass spectrometry. Multivariate statistics (PCA, Random Forest) and rule-based peak detection ensured robust compound identification and quantitation.

Used Instrumentation

• GCMS with triple quadrupole mass spectrometer and HS-20 headspace sampler
• GC-MS/MS (GCMS-TQ 8040 and GCMS-TQ 8040 NX)
• Smart Metabolites Database™ and LabSolutions Insight™ software
• LC-MS/MS platform (Nexera X2 and LCMS-8060) using positive/negative ESI and MRM

Main Results and Discussion

• Aroma profiling of three sake categories (futsu-shu, junmai-shu, daiginjo-shu) identified 86 volatiles. PCA score plots cleanly separated the products and loading plots revealed class-specific markers such as distinct esters and alcohols.
• Metabolite analysis of the same sake samples detected 149 derivatized hydrophilic compounds. Multivariate analysis again resolved the three sake types, pinpointing sugar, organic acid and amino acid differences linked to polishing grade and addition of brewer’s alcohol.
• Geographical origin of 106 asparagus samples was assessed by measuring up to 337 hydrophilic metabolites. After z-score normalization and outlier removal, a Random Forest model built on 13 key compounds achieved 91.7% accuracy in classifying domestic vs. foreign origin.
• Deterioration testing on two sake samples and white wine under refrigerated, light-exposed, heated and shaken conditions revealed minimal drift by PCA. One-way ANOVA highlighted four metabolites sensitive to mild thermal/light stress: methionine sulfoxide (oxidation marker), uric acid, cysteine (precursor of off-odors), and the tryptophan–kynurenine pair (indicative of oxidative catabolism).

Benefits and Practical Applications of the Method

By integrating metabolomics into quality control workflows, food producers can:

• Objectively monitor flavor and freshness
• Authenticate product origin and detect adulteration
• Optimize processing parameters and storage conditions
• Identify early oxidative or microbial spoilage markers

Future Trends and Potential Applications

Emerging directions include:

• High-throughput, non-targeted metabolomics with machine-learning classifiers
• Real-time in-line monitoring using miniaturized MS
• Integration with genomics and proteomics for systems-level food profiling
• Expanded public and proprietary metabolite libraries for diverse food matrices
• Predictive shelf-life models and digital twin simulations

Conclusion

Shimadzu’s combination of precise instrumentation, robust databases and advanced data analysis delivers reliable metabolomic insights that elevate food safety, quality and traceability. The case studies demonstrate how targeted and non-targeted metabolite profiling can guide product development, authentication and shelf-life management across the food and beverage industry.