Partial Least-Squares-Discriminant Analysis Differentiating Chinese Wolfberries by UPLC鈥揗S and Flow Injection Mass Spectrometric (FIMS) Fingerprints
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- 作者：Weiying Lu ; Qianqian Jiang ; Haiming Shi ; Yuge Niu ; Boyan Gao ; Liangli (Lucy) Yu
- 刊名：Journal of Agricultural and Food Chemistry
- 出版年：2014
- 出版时间：September 17, 2014
- 年：2014
- 卷：62
- 期：37
- 页码：9073-9080
- 全文大小：366K
- ISSN：1520-5118
文摘
Lycium barbarum L. fruits (Chinese wolfberries) were differentiated for their cultivation locations and the cultivars by ultraperformance liquid chromatography coupled with mass spectrometry (UPLC鈥揗S) and flow injection mass spectrometric (FIMS) fingerprinting techniques combined with chemometrics analyses. The partial least-squares-discriminant analysis (PLS-DA) was applied to the data projection and supervised learning with validation. The samples formed clusters in the projected data. The prediction accuracies by PLS-DA with bootstrapped Latin partition validation were greater than 90% for all models. The chemical profiles of Chinese wolfberries were also obtained. The differentiation techniques might be utilized for Chinese wolfberry authentication.