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UPLC–Q-TOF/MS-based untargeted metabolomics coupled with chemometrics approach for Tieguanyin tea with seasonal and year variations

2019; Elsevier BV; Volume: 283; Linguagem: Inglês

10.1016/j.foodchem.2019.01.050

1873-7072

Peng Zhou, Ou Hu, Haiyan Fu, Li-Qun Ouyang, Xuedong Gong, Peng Meng, Zheng Wang, Ming Dai, Xiaoming Guo, Ying Wang,

Traditional Chinese Medicine Analysis

The taste and aroma quality of Tieguanyin tea fluctuate seasonally and yearly. However, the compounds responsible for the seasonal and year variations of metabolic pattern and its sensory quality are far from clear. 60 Tieguanyin tea samples harvested in different years and seasons were analyzed by ultraperformance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC–Q-TOF/MS) and chemometrics. Principal component analysis (PCA) explained 33.2% of the total variance, while orthogonal projection to latent structures discriminate analysis (OPLS-DA) can obtain potential metabolites with better discrimination, and with R2X and Q2 of cross-validation as 0.974 and 0.937, respectively. Subsequently, heat map analysis (HCA) visualized relationships between Tieguanyin teas with these significantly different potential metabolites by Mann-Whitney U test (p < 0.05). Furthermore, the best discriminate metabolites contributing to different sensory qualities were revealed by stepwise liner discrimination analysis (SLDA) with 100% accuracy rate. The present strategy also exhibited great potential for untargeted metabolomics of other foods.