Title of article :
Statistical analysis for improving data precision in the SPME GC–MS analysis of blackberry (Rubus ulmifolius Schott) volatiles
Author/Authors :
D’Agostino، نويسنده , , M.F. and Sanz، نويسنده , , J. and Mart?nez-Castro، نويسنده , , I. and Giuffrè، نويسنده , , A.M. and Sicari، نويسنده , , V. and Soria، نويسنده , , A.C.، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2014
Pages :
9
From page :
248
To page :
256
Abstract :
Statistical analysis has been used for the first time to evaluate the dispersion of quantitative data in the solid-phase microextraction (SPME) followed by gas chromatography–mass spectrometry (GC–MS) analysis of blackberry (Rubus ulmifolius Schott) volatiles with the aim of improving their precision. Experimental and randomly simulated data were compared using different statistical parameters (correlation coefficients, Principal Component Analysis loadings and eigenvalues). Non-random factors were shown to significantly contribute to total dispersion; groups of volatile compounds could be associated with these factors. A significant improvement of precision was achieved when considering percent concentration ratios, rather than percent values, among those blackberry volatiles with a similar dispersion behavior. elty over previous references, and to complement this main objective, the presence of non-random dispersion trends in data from simple blackberry model systems was evidenced. Although the influence of the type of matrix on data precision was proved, the possibility of a better understanding of the dispersion patterns in real samples was not possible from model systems. proach here used was validated for the first time through the multicomponent characterization of Italian blackberries from different harvest years.
Keywords :
Solid-phase microextraction (SPME) , Gas chromatography–mass spectrometry (GC–MS) , volatiles , Statistical analysis , Precision , Blackberry (Rubus ulmifolius Schott)
Journal title :
Talanta
Serial Year :
2014
Journal title :
Talanta
Record number :
1670892
Link To Document :
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