μ‐PESI ‐based MS Profiling Combined with Untargeted Metabolomics Analysis for Rapid Identification of Red Wine Geographical Origin
Keyuan Pu, Yue Wang, Huiwen Wei, Jun Hu, Jiamin Qiu, Siyu Chen, Qian Liu, Yan Lin, Kwan‐Ming Ng - Nutrition and Dietetics
- Agronomy and Crop Science
- Food Science
- Biotechnology
Abstract
BACKGROUND
The commercial value of red wine is strongly linked to the geographical origin. Given the large global market, there is great demand for high‐throughput screening methods to authenticate the geographical source of red wine. However, only limited techniques have been established up to now.
RESULTS
Herein, a sensitive and robust method, namely probe electrospray ionization mass spectrometry (μ‐PESI‐MS), was established to achieve the rapid analysis at approximately 1.2 mins/sample without any pretreatment. A scotch near the needle tip provides a fixed micro‐volume for each analysis to achieve satisfactory ion signal reproducibility (RSD < 26.7%). In combining with machine learning algorithm, 16 characteristic ions were discovered from thousands detected ions and were utilized for differentiating the red wine origins. Among them, the relative abundances of two characteristic metabolites (trigonelline and proline) correlated to geographical conditions (sun exposure and water stress) were identified, providing the rationale for the differentiation of the geographical origins.
CONCLUSION
The proposed μ‐PESI‐MS based method demonstrates promising high‐throughput determination capability in red wine traceability.
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