Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 62, Issue 37, Pages 9073-9080Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jf502156n
Keywords
Lycium barbarum L.; Chinese wolfberry; ultraperformance liquid chromatography; flow injection mass spectrometry; partial least-squares-discriminant analysis
Funding
- National High Technology Research and Development Program of China [2013AA102202, 2013AA102207]
- special fund for Agro-scientific Research in the Public Interest [201203069]
- SJTU startup fund for young talent [13X100040047]
- SJTU 985-III disciplines platform and talent fund [TS0414115001, TS0320215001]
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Lycium barbarum L. fruits (Chinese wolfberries) were differentiated for their cultivation locations and the cultivars by ultraperformance liquid chromatography coupled with mass spectrometry (UPLC-MS) 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.
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