Partial least-squares-discriminant analysis differentiating Chinese wolfberries by UPLC-MS and flow injection mass spectrometric (FIMS) fingerprints

Weiying Lu; Qianqian Jiang; Haiming Shi; Yuge Niu; Boyan Gao; Liangli Lucy Yu

doi:10.1021/jf502156n

Partial least-squares-discriminant analysis differentiating Chinese wolfberries by UPLC-MS and flow injection mass spectrometric (FIMS) fingerprints

J Agric Food Chem. 2014 Sep 17;62(37):9073-80. doi: 10.1021/jf502156n. Epub 2014 Sep 2.

Authors

Weiying Lu¹, Qianqian Jiang, Haiming Shi, Yuge Niu, Boyan Gao, Liangli Lucy Yu

Affiliation

¹ Institute of Food and Nutraceutical Science, School of Agriculture and Biology, Shanghai Jiao Tong University , Shanghai 200240, China.

PMID: 25152955
DOI: 10.1021/jf502156n

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.

Keywords: Chinese wolfberry; Lycium barbarum L.; flow injection mass spectrometry; partial least-squares-discriminant analysis; ultraperformance liquid chromatography.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China
Chromatography, High Pressure Liquid*
Discriminant Analysis
Flow Injection Analysis
Food Contamination / analysis
Fruit / chemistry
Fruit / classification
Least-Squares Analysis
Lycium / chemistry*
Lycium / classification*
Mass Spectrometry / methods*