Discrimination of geographical origin of oranges (Citrus sinensis L. Osbeck) by mass spectrometry-based electronic nose and characterization of volatile compounds.

An untargeted method using headspace solid-phase microextraction coupled to electronic nose based on mass spectrometry (HS-SPME/MS-eNose) in combination with chemometrics was developed for the discrimination of oranges of three geographical origins (Italy, South Africa and Spain). Three multivariate statistical models, i.e. PCA/LDA, SELECT/LDA and PLS-DA, were built and relevant performances were compared. Among the tested models, SELECT/LDA provided the highest prediction abilities in cross-validation and external validation with mean values of 97.8% and 95.7%, respectively. Moreover, HS-SPME/GC-MS analysis was used to identify potential markers to distinguish the geographical origin of oranges. Although 28 out of 65 identified VOCs showed a different content in samples belonging to different classes, a pattern of analytes able to discriminate simultaneously samples of three origins was not found. These results indicate that the proposed MS-eNose method in combination with multivariate statistical analysis provided an effective and rapid tool for authentication of the orange's geographical origin.

Isotope ratio mass spectrometry in combination with chemometrics for characterization of geographical origin and agronomic practices of table grape.

BACKGROUND: Although table grape is one of the most cultivated and consumed fruits worldwide, no study has been reported on its geographical origin or agronomic practice based on stable isotope ratios. This study aimed to evaluate the usefulness of isotopic ratios (i.e. 2 H/1 H, 13 C/12 C, 15 N/14 N and 18 O/16 O) as possible markers to discriminate the agronomic practice (conventional versus organic farming) and provenance of table grape. RESULTS: In order to quantitatively evaluate which of the isotopic variables were more discriminating, a t test was carried out, in light of which only δ13 C and δ18 O provided statistically significant differences (P ≤ 0.05) for the discrimination of geographical origin and farming method. Principal component analysis (PCA) showed no good separation of samples differing in geographical area and agronomic practice; thus, for classification purposes, supervised approaches were carried out. In particular, general discriminant analysis (GDA) was used, resulting in prediction abilities of 75.0 and 92.2% for the discrimination of farming method and origin respectively. CONCLUSION: The present findings suggest that stable isotopes (i.e. δ18 O, δ2 H and δ13 C) combined with chemometrics can be successfully applied to discriminate the provenance of table grape. However, the use of bulk nitrogen isotopes was not effective for farming method discrimination. © 2016 Society of Chemical Industry.