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Poster Presentations
Day 2, June 23（Mon.）
Room P (Maesato East, Foyer, Ocean Wing)
- 2P-AM-27
Application of LC-MS-Based Metabolomics and Proteomics for Bee Pollen Authentication and Food Fraud Prevention
(NCHU)
oYa-Ting Pan, Chun-Sheng Wang, Chien-Chen Lai
Due to increasing public awareness of health and changing in dietary habits, bee pollen has gained growing attention since it's rich in nutrients and various bioactive compounds. Bee pollen is one of the major targets of food fraud in bee products. The study aimed to classify bee pollen based on floral variety, origin, and production year using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS) combined with untargeted metabolomics and proteomics. In untargeted metabolomic study, data processing is performed using the in-house integrated full-scan and data-dependent acquisition (IFSDDA) mode. The results effectively differentiate bee pollen based on polyphenols, flavonoids, and fatty acids. In the proteomic research, this study optimized various extraction methods, enzymatic digestion strategies, chromatographic gradients, and internal standard contents for bee pollen analysis. The future research will apply these optimized conditions to real samples. In conclusion, this study successfully established an LC-MS-based analytical method for metabolomic and proteomic analysis of bee pollen, effectively distinguishing different types of bee pollen through metabolite profiling so far. Further analysis of differentially expressed proteins (DEPs) will be conducted to enhance classification accuracy.