Trace Detection of Aspartame in Beverages

Significance of the topic

Aspartame is a widely used artificial sweetener offering low-calorie sweetness in beverage and food products. Concern over potential health risks has driven the need for rapid, sensitive detection methods to ensure regulatory compliance and consumer safety.

Objectives and overview of the study

This study demonstrates a streamlined surface-enhanced Raman spectroscopy (SERS) approach using the Metrohm Instant SERS Analyzer (MISA) to detect trace levels of aspartame in carbonated water and diet cola. The method aims to achieve minimal sample preparation, high sensitivity, and field-deployable operation.

Methodology and used instrumentation

A pure aspartame standard was used to generate a reference SERS spectrum with gold nanoparticles (Au NPs). Beverage samples were prepared by spiking carbonated water at concentrations ranging from 100 ng/mL to 100 µg/mL and diluting diet cola tenfold. Each sample was mixed with Au NPs and NaCl, then analyzed using MISA with the following settings:

• Instrument: MISA Advanced with Vial Attachment
• Au NP SERS ID Kit
• Laser power: 5
• Integration time: 1 s
• Averages: 10
• Orbital raster scan: on

Main results and discussion

SERS spectra revealed a detection limit of 100 ng/mL for aspartame in spiked carbonated water, with clear signal-to-noise performance across the concentration range. In tenfold diluted diet cola, aspartame was detected between 10–50 µg/mL, aligning with typical formulation levels. The minimal sample treatment effectively reduced matrix interferences.

Benefits and practical applications

The described SERS-based assay offers:

• Rapid on-site testing without extensive laboratory infrastructure
• Minimal sample preparation by simple dilution and mixing
• High sensitivity suitable for regulatory and quality control analysis
• Portability for use in low-resource or field environments

Future trends and opportunities

Advances in nanoparticle substrates, portable Raman systems, and data analysis algorithms may further improve detection sensitivity and specificity. Integration with machine learning for automated spectral interpretation, multiplexed detection of multiple additives, and connectivity to cloud platforms can expand applications in food safety monitoring.

Conclusion

The MISA SERS method with Au nanoparticles provides a fast, sensitive, and portable approach for detecting trace aspartame in beverages. Its ease of use and minimal resource requirements make it an effective tool for routine quality control and field screening of food additives.