化学计量学
化学
偏最小二乘回归
色谱法
绿茶
质谱法
线性判别分析
轨道轨道
化学成分
食品科学
数学
人工智能
计算机科学
统计
作者
Jiayi Zhong,Ning Chen,Sichen Huang,Xiaowei Fan,Yi Zhang,Dabing Ren,Lunzhao Yi
出处
期刊:Food Chemistry
[Elsevier BV]
日期:2020-04-20
卷期号:326: 126760-126760
被引量:55
标识
DOI:10.1016/j.foodchem.2020.126760
摘要
To reveal the characteristic chemical profiles of Pu-erh raw tea (PRT) and traditional green tea (TGT), a high-throughput analytical method based on UPLC-Q-Orbitrap-MS/MS was proposed. 145 components were characterized with a three-level qualitative strategy and the integrated filtering strategy combining nitrogen rule, mass defect, and diagnostic ions information. 124 components were quantified using an internal standard method. The total contents of flavan-3-ols and derivatives, phenolic acids and derivatives were higher in PRT than TGT, while flavonoids were reversed. Furthermore, partial least squares-discriminant analysis (PLS-DA) models were established to classify TGT and PRT. 23 characteristic components were revealed by variable importance in projection method. Their difference in content is between 1.5 and 7.3 times for PRT and TGT. The results showed the chemical characteristics of TGT and PRT clearly and comprehensively. The high-throughput method demonstrated considerable potential in the analysis of complex chemical system, such as food and herbs.
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