Authenticity verification and quality assessment of Taiwan Oriental Beauty oolong tea with a volatilomic strategy

• Volatile profiling of Oriental Beauty tea used for origin discrimination. • 37 volatiles were selected from thousands based on VIP score distribution. • Blind samples were correctly determined as Oriental Beauty. • Sensory evaluation revealed 8 consistent volatiles including linalool-related ones. • The study proposed strategies to detect fraud in tea authenticity and quality. Taiwan Oriental Beauty oolong tea is highly valued for its distinctive aroma and flavor, but is at risk of adulteration due to its high cost and scarcity. This study aims to achieve volatile profiling of Oriental Beauty oolong tea for further origin discrimination, blind sample testing and quality grade categorization. The inspection of tea volatile compounds (VCs) is accomplished by means of headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). A total of 38 samples were prepared by mixing 0.5 g tea leaf powder with 0.06 g salt, 1 mL boiling water, and 10 μL of 5 ppm 2-nonanone. After the 5-minute equilibration at 90°C, volatiles were extracted for 20 minutes using a DVB/CAR/PDMS fiber and analyzed within 40.5 minutes. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) effectively distinguished between Oriental Beauty oolong teas and overseas teas, screening out 37 significant metabolites for geographical source. The multivariate models also assisted in better accuracy of blinded samples determination. Interestingly, ethyl 2-(5-methyl-5-vinyltetrahydrofuran-2-yl) propan-2-yl carbonate, phenylethyl alcohol, 3,7-dimethyl-1,5,7-octatrien-3-ol, methyl salicylate, benzyl alcohol, benzaldehyde and linalool-related compounds showed strong consistency in tea grades sensory evaluation. In conclusion, the optimized volatilomic strategy demonstrates strong potential for the authentication and grading of Oriental Beauty oolong tea. However, further validation with larger sample sets and seasonal variations is recommended to enhance robustness and expand applicability across broader tea varieties.