title: Partial least-squares-discriminant analysis differentiating Chinese wolfberries by UPLC-MS and flow injection mass spectrometric (FIMS) fingerprints.
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.
authors.affiliation: Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University , Shanghai 200240, China.
authors.forename: Weiying
authors.initials: W
authors.lastname: Lu
authors.forename: Qianqian
authors.initials: Q
authors.lastname: Jiang
authors.forename: Haiming
authors.initials: H
authors.lastname: Shi
authors.forename: Yuge
authors.initials: Y
authors.lastname: Niu
authors.forename: Boyan
authors.initials: B
authors.lastname: Gao
authors.forename: Liangli Lucy
authors.initials: LL
authors.lastname: Yu
mesh_terms: D002681:China; D002851:Chromatography, High Pressure Liquid; D016002:Discriminant Analysis; D017022:Flow Injection Analysis; D005506:Food Contamination / Q000032:analysis; D005638:Fruit / Q000737:chemistry / Q000145:classification; D016018:Least-Squares Analysis; D032305:Lycium / Q000737:chemistry* / Q000145:classification*; D013058:Mass Spectrometry / Q000379:methods*
keywords: Chinese wolfberry; Lycium barbarum L.; flow injection mass spectrometry; partial least-squares-discriminant analysis; ultraperformance liquid chromatography