Application of RADIAN ASAP-LiveID Platform in Flavor Type Discrimination of Chinese Baijiu and Authentication of Maotai

Significance of the Topic

Chinese Baijiu represents one of the world’s oldest and most diverse distilled spirits, characterized by unique fermentation processes and flavor components. Rapid and reliable discrimination of flavor types and authentication of premium varieties such as Maotai are critical for quality control, regulatory compliance, and protection of brand integrity in the spirits industry.

Objectives and Study Overview

This study employs the RADIAN ASAP-LiveID platform to achieve two primary goals

• Discriminate among six major Chinese Baijiu flavor types based on direct mass spectrometry fingerprints
• Authenticate Maotai samples and detect counterfeit products in a near real time manner

Methodology and Instrumentation Used

The RADIAN ASAP system couples an Atmospheric Solids Analysis Probe with single quadrupole mass spectrometry for direct sample ionization without preparation. Key parameters included a 40–250 Da mass range, 600 °C desolvation temperature, and 15 V cone voltage. LiveID software integrated PCA-LDA chemometric modeling to classify samples and perform leave 20 percent out cross validation. Sample introduction involved pipetting five microliters of Baijiu onto the ASAP capillary for immediate analysis.

Main Results and Discussion

PCA-LDA modeling based on 20 principal components and five discriminant functions achieved clear separation of sauce, strong, light, sesame, feng and laobaigan flavor types, with an overall cross validation accuracy of 93.6 percent. Supermarket samples were correctly assigned to their declared flavor categories within seconds. Authentication of Maotai against other sauce-flavor Baijiu revealed elevated pyrazine markers, notably tetramethylpyrazine at m/z 137. Non Maotai samples were identified as outliers, demonstrating the method’s specificity.

Benefits and Practical Applications

The RADIAN ASAP-LiveID approach delivers rapid, minimal preparation screening suitable for production monitoring, raw material verification, and food authenticity testing. Its compact design and real time results facilitate deployment in quality assurance laboratories, regulatory agencies, and field inspections.

Future Trends and Potential Applications

Advances in ambient ionization and machine learning are expected to further enhance sensitivity and expand to other beverage and food matrices. Integration with high resolution mass analyzers and comprehensive spectral libraries will support broader metabolite profiling and traceability studies.

Conclusion

The RADIAN ASAP-LiveID platform provides a robust, rapid solution for discriminating Baijiu flavor types and authenticating Maotai. Its direct analysis capability and chemometric modeling combine to offer an efficient tool for industry quality control and regulatory enforcement.

References

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