classification of Vegetable Oils by
Linear Discriminant Analysis based on Mass Spectrometic Data
Institute of Chemistry, Chemical Research Center, Hungarian Academy
of Sciences, P.O. Box 17, H-1525, Hungary,
E-mail: janna@chemres.hu, Tel.: +36-1-325-79-00/261
The main triacylglycerol (TAG) composition of different plant oils (almond, avocado, corn germ, grape seed, linseed, mustard seed, olive, peanut, pumpkinseed, sesame seed, soybean, sunflower, walnut and wheat germ) were analyzed using two different mass spectrometric techniques: high-performance liquid chromatography-atmospheric pressure chemical ionization mass spectrometry (HPLC-APCI-MS) and matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF-MS).
HPLC-APCI-MS measurements were performed using gradient elution technique with acetone-acetonitrile eluent systems on an ODS column (Purospher, RP-18e, 125x4 mm, 5 μm). The relative TAG content of the different plant oils was calculated from ion chromatograms extracted from HPLC-APCI-MS results, and from spectra obtained by MALDI-TOF-MS for the linear discriminant analysis (LDA).
LDA as a multivariate mathematical
statistical method was used to distinguish the different plant oils based on
their TAG composition. LDA resulted that more
than 90% of the samples was classified correctly based on APCI-MS data.
Expressive score plots of the LDA calculations can be observed with both LDA
calculations based APCI- and MALDI-MS data. Comparing the two MS methods,
MALDI-MS provides much shorter analysis and data processing time than
HPLC-APCI-MS.