In this study the effective discrimination of extra virgin olive oils is described using HPLC–MS, combined with chemometric evaluation. The presented method is simple since the diluted oil sample is directly injected into the system, without any preliminary chemical derivatization or purification step. Separation of diacylglycerols, triacylglycerols and sterols occurs within 20 min and is achieved using an octadecyl-silica column. Detection is performed by positive APCI mass spectrometry which provided sensitivity to detect over 50 compounds in the sample. After extraction of data, stepwise discriminant function analysis is used to select the variables with the highest discriminative power. These variables are used to perform linear discriminant analysis and classify/predict the samples. One-hundred per cent classification and 99% prediction rate was achieved for olive oils obtained from Nocellara, Biancolilla and Cerausola cultivars. Reliability of prediction was tested by cross validation.

NAGY, K., BONGIORNO, D., AVELLONE, G., AGOZZINO, P., CERAULO, L., VEKEY, K. (2005). High Performance Liquid Chromatografy-Mass Spectrometry based chemometric characterization of olive oils. JOURNAL OF CHROMATOGRAPHY A, 1078, 90-97 [10.1016/J.CHROMA.2005.05.008].

High Performance Liquid Chromatografy-Mass Spectrometry based chemometric characterization of olive oils

BONGIORNO, David;AVELLONE, Giuseppe;AGOZZINO, Pasquale;CERAULO, Leopoldo;
2005-01-01

Abstract

In this study the effective discrimination of extra virgin olive oils is described using HPLC–MS, combined with chemometric evaluation. The presented method is simple since the diluted oil sample is directly injected into the system, without any preliminary chemical derivatization or purification step. Separation of diacylglycerols, triacylglycerols and sterols occurs within 20 min and is achieved using an octadecyl-silica column. Detection is performed by positive APCI mass spectrometry which provided sensitivity to detect over 50 compounds in the sample. After extraction of data, stepwise discriminant function analysis is used to select the variables with the highest discriminative power. These variables are used to perform linear discriminant analysis and classify/predict the samples. One-hundred per cent classification and 99% prediction rate was achieved for olive oils obtained from Nocellara, Biancolilla and Cerausola cultivars. Reliability of prediction was tested by cross validation.
2005
NAGY, K., BONGIORNO, D., AVELLONE, G., AGOZZINO, P., CERAULO, L., VEKEY, K. (2005). High Performance Liquid Chromatografy-Mass Spectrometry based chemometric characterization of olive oils. JOURNAL OF CHROMATOGRAPHY A, 1078, 90-97 [10.1016/J.CHROMA.2005.05.008].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/3600
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