The Use of HRMS and Statistical Analysis in the Investigation of Basmati Rice Authenticity and Potential Food Fraud

Importance of the Topic

Food fraud involving basmati rice undermines consumer confidence and has economic implications for producers and retailers. Authentic basmati is characterized by unique geographic origin and aromatic profile. Reliable verification methods are essential for food safety, quality control and regulatory compliance.

Study Objectives and Overview

This work demonstrates a proof of principle method to evaluate basmati rice authenticity using non targeted volatile compound profiling. The approach integrates high resolution mass spectrometry with multivariate statistics to discern genuine basmati from adulterated or look alike long grain and jasmine rice varieties.

Methodology and Instrumentation

Volatile compounds were extracted from dried rice samples via heated solid phase microextraction headspace. Separation was performed on a 30 m DB-5 GC column. A Waters SYNAPT G2-Si mass spectrometer operated in HDMSE mode with atmospheric pressure gas chromatography (APGC) provided accurate mass precursor and fragment ion data combined with ion mobility separation. Data alignment, peak detection and statistical analysis (PCA, OPLS-DA, correlation analysis) were conducted using Progenesis QI informatics software.

Instrumental Setup

• SPME fiber assembly (DVB/CAR/PDMS) for headspace extraction at 120 °C
• 7890A GC system with DB-5MS column (30 m × 0.25 mm × 0.25 μm)
• Waters SYNAPT G2-Si HDMS operated in E mode with collision energy ramp
• Progenesis QI for data processing and Progenesis Metascope for database searches

Results and Discussion

A total of 3885 compounds were detected across samples. PCA revealed distinct clustering of basmati, jasmine and long grain rice, with two basmati samples clustering with other varieties from the same producer. OPLS-DA identified key marker ions differentiating basmati from long grain rice. Correlation analysis further isolated over 50 basmati-specific markers and 26 long grain related markers. Trend plots demonstrated reproducible marker abundance profiles and highlighted sample origin influences.

Practical Benefits and Applications

The combination of APGC, HDMSE and Progenesis QI streamlines non targeted screening workflows, enhancing specificity and sensitivity. The approach offers a data rich platform for food fraud detection, with potential to develop targeted pass/fail assays for routine quality control laboratories using simpler instrumentation.

Future Trends and Opportunities

Further validation with a larger set of authenticated and non authenticated samples is needed to establish robust marker panels. Integration of embedded elemental composition calculations and online database searching will accelerate compound identification. Adaptation to tandem quadrupole platforms could facilitate routine screening in industrial settings.

Conclusion

This study demonstrates a high resolution mass spectrometry and statistical analysis workflow capable of distinguishing authentic basmati rice from adulterated samples. The method provides a strong foundation for developing rapid, reliable food authenticity tests, pending further validation with well characterized samples.

References

1. Prabha Jagannathan The Economic Times Basanti export adulteration leaves bad taste in mouth 2007
2. Fletcher A Food Standard Agency report on basmati regulations 2005
3. Waters SYNAPT G2-Si product brochure Part No 720004681EN
4. Waters APGC White Paper Part No 720004771EN