Thirty samples of virgin olive oil were analysed by sensory and instrumental methods. Free-choice profiling and quantitative descriptive analysis were used for aroma analysis, and GC-MS was used for analysis of headspace volatiles. Principal component analysis and partial least squares regression analysis were used for relating sensory and instrumental data. Similar clusters of samples were obtained from principal components analyses of both data sets. Partial least squares regression made good predictions from headspace data of some of the descriptors used in quantitative descriptive analysis. The prediction of cut grass aroma was obtained, in particular, from 5 unidentified compounds. The 5 compounds had similar mass spectra, but GC-sniffport analysis showed that only one of them (possibly isomers or homologues) gave an aroma that could be related to the cut grass descriptor.
Sensory charactetisation of virgin olive oil and realtionship with headspace composition.
SERVILI, Maurizio;
1995
Abstract
Thirty samples of virgin olive oil were analysed by sensory and instrumental methods. Free-choice profiling and quantitative descriptive analysis were used for aroma analysis, and GC-MS was used for analysis of headspace volatiles. Principal component analysis and partial least squares regression analysis were used for relating sensory and instrumental data. Similar clusters of samples were obtained from principal components analyses of both data sets. Partial least squares regression made good predictions from headspace data of some of the descriptors used in quantitative descriptive analysis. The prediction of cut grass aroma was obtained, in particular, from 5 unidentified compounds. The 5 compounds had similar mass spectra, but GC-sniffport analysis showed that only one of them (possibly isomers or homologues) gave an aroma that could be related to the cut grass descriptor.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
