Off-favour Analysis in Food Using a Simple and Rapid SPME-GC/TQMS Method with Dedicated Off-favour Database

Importance of the Topic

Off-flavour compounds in food not only degrade sensory quality but can also signal microbial activity or chemical breakdown linked to safety risks. A rapid, broadly applicable method to detect these volatile markers supports quality control in research, industrial and regulatory environments.

Study Objectives and Overview

This work presents a generic solid phase micro-extraction (SPME) coupled with gas chromatography triple quadrupole mass spectrometry (GC/TQMS) workflow. Leveraging a dedicated off-flavour database and fully automated sampling, the study aims to identify and semi-quantify off-flavour volatiles in diverse food matrices under spoilage conditions.

Methodology

Four representative foods—watermelon juice, milk (liquid); cream cheese (semi-solid); and lettuce (solid)—were stored at room temperature for three days to induce spoilage. Control samples were held at 4 °C. Headspace volatiles were extracted by SPME (DVB/CAR/PDMS fibre) at 80 °C for 30 min with agitation, then desorbed at 270 °C into the GC/TQMS system. Chromatographic separation used a polar wax column with a temperature program from 50 °C to 250 °C. Data acquisition employed scan and multiple reaction monitoring (MRM) modes, and fold-change analysis was performed in MetaboAnalyst 3.0.

Used Instrumentation

• Fabre: Divinylbenzene/Carboxen/Polydimethylsiloxane 50/30 µm
• Autosampler: Shimadzu AOC-6000 with SPME module
• GC/TQMS: Shimadzu GCMS-TQ8040 triple quadrupole
• Column: InertCap Pure-Wax 30 m × 0.25 mm × 0.25 µm
• Carrier Gas: Helium, constant pressure mode (83.5 kPa)

Main Results and Discussion

Spoiled samples showed substantial increases in characteristic volatiles. In watermelon juice, acetic acid was the most elevated marker among 34 upregulated compounds, reflecting sugar fermentation. Milk spoilage yielded 31 elevated volatiles including butyric, caproic and caprylic acids from triglyceride hydrolysis, plus sulfur derivatives (dimethyl disulphide) and indole from amino acid degradation. Cream cheese exhibited a 1.5-fold rise in short-chain fatty acids (isobutyric, isovaleric acids) likely from lipase action on fats. Lettuce spoilage led to 47 increased and 8 decreased compounds; microbial metabolism produced 2-ethyl-1-hexanol, p-ethylguaiacol, and fermentation products such as ethyl acetate.

Benefits and Practical Applications

• Solvent-free, non-destructive headspace sampling
• Automated workflow enabling high throughput
• Applicability across liquid, semi-solid and solid foods
• Targeted screening using an off-flavour spectral library
• Supports quality assurance and spoilage diagnostics

Future Trends and Opportunities

Advances may include expansion of off-flavour databases, integration with real-time monitoring, miniaturized sampling devices, coupling with ion mobility MS or high-resolution systems, and predictive models for spoilage onset. Applications could extend to novel food matrices, packaging interaction studies and shelf‐life prediction.

Conclusion

The described SPME-GC/TQMS approach with a dedicated off-flavour library offers a rapid, flexible and reliable tool for detecting spoilage markers in diverse food types, facilitating both research into biochemical pathways and practical quality control.

References

1. Ridgway K, Lalljie SPD, Smith RM. Analysis of Food Taints and Off-Flavours: A Review. Food Additives & Contaminants. 2009;27(2):146–168.
2. Xia J, Wishart DS. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis. Current Protocols in Bioinformatics. 2016;55:14.10.1–14.10.91.