期刊
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
卷 56, 期 14, 页码 5451-5456出版社
AMER CHEMICAL SOC
DOI: 10.1021/jf072402x
关键词
honey; NMR; metabolomics; genetic programming; PLS; geographical origin; food authenticity; chemometrics
Proton nuclear magnetic resonance spectroscopy (H-1 NMR) and multivariate analysis techniques have been used to classify honey into two groups by geographical origin. Honey from Corsica (Miel de Corse) was used as an example of a protected designation of origin product. Mathematical models were constructed to determine the feasibility of distinguishing between honey from Corsica and that from other geographical locations in Europe, using H-1 NMR spectroscopy. Honey from 10 different regions within five countries was analyzed. H-1 NMR spectra were used as input variables for projection to latent structures (PLS) followed by linear discriminant analysis (LDA) and genetic programming (GP). Models were generated using three methods, PLS-LDA, two-stage GP, and a combination of PLS and GP (PLS-GP). The PLS-GP model used variables selected by PLS for subsequent GP calculations. All models were generated using Venetian blind cross-validation. Overall classification rates for the discrimination of Corsican and non-Corsican honey of 75.8, 94.5, and 96.2% were determined using PLS-LDA, two-stage GP, and PLS-GP, respectively. The variables utilized by PLS-GP were related to their H-1 NMR chemical shifts, and this led to the identification of trigonelline in honey for the first time.
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