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Partial Least-Squares-Discriminant Analysis Differentiating Chinese Wolfberries by UPLC–MS and Flow Injection Mass Spectrometric (FIMS) Fingerprints
- Source :
- Journal of Agricultural and Food Chemistry. 62:9073-9080
- Publication Year :
- 2014
- Publisher :
- American Chemical Society (ACS), 2014.
-
Abstract
- 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.
- Subjects :
- China
Chromatography
Chemistry
Discriminant Analysis
Food Contamination
General Chemistry
Lycium
Mass spectrometry
Linear discriminant analysis
Mass spectrometric
Mass Spectrometry
Chemometrics
Data projection
Wolfberries
Fruit
Flow Injection Analysis
Partial least squares regression
Uplc ms ms
Least-Squares Analysis
General Agricultural and Biological Sciences
Chromatography, High Pressure Liquid
Subjects
Details
- ISSN :
- 15205118 and 00218561
- Volume :
- 62
- Database :
- OpenAIRE
- Journal :
- Journal of Agricultural and Food Chemistry
- Accession number :
- edsair.doi.dedup.....e5cd45e3e5e599fb0c8c2ac8b59ce264