Electronic nose and isotope ratio mass spectrometry in combination
with chemometrics for the characterization of the geographical
origin of Italian sweet cherries
Sweet cherries from two Italian regions, Apulia and Emilia Romagna, were analysed using electronic nose
(EN) and isotope ratio mass spectrometry (IRMS), with the aim of distinguishing them according to their
geographic origin. The data were elaborated by statistical techniques, examining the EN and IRMS datasets
both separately and in combination. Preliminary exploratory overviews were performed and then
linear discriminant analyses (LDA) were used for classification. Regarding EN, different approaches for
variable selection were tested, and the most suitable strategies were highlighted. The LDA classification
results were expressed in terms of recognition and prediction abilities and it was found that both EN and
IRMS performed well, with IRMS showing better cross-validated prediction ability (91.0%); the EN–IRMS
combination gave slightly better results (92.3%). In order to validate the final results, the models were
tested using an external set of samples with excellent results
