| Title: | Discrimination of geographical origin of oranges (Citrus sinensis L. Osbeck) by mass spectrometry-based electronic nose and characterization of volatile compounds |
| Author(s): | Centonze V; Lippolis V; Cervellieri S; Damascelli A; Casiello G; Pascale M; Logrieco AF; Longobardi F; |
| Address: | "Dipartimento di Chimica, Universita di Bari 'Aldo Moro', Via Orabona 4, 70126 Bari, Italy. Institute of Sciences of Food Production (ISPA), National Research Council of Italy (CNR), Via G. Amendola 122/O, 70126 Bari, Italy. Electronic address: vincenzo.lippolis@ispa.cnr.it. Institute of Sciences of Food Production (ISPA), National Research Council of Italy (CNR), Via G. Amendola 122/O, 70126 Bari, Italy. Dipartimento di Chimica, Universita di Bari 'Aldo Moro', Via Orabona 4, 70126 Bari, Italy; Institute of Sciences of Food Production (ISPA), National Research Council of Italy (CNR), Via G. Amendola 122/O, 70126 Bari, Italy" |
| DOI: | 10.1016/j.foodchem.2018.10.105 |
| ISSN/ISBN: | 1873-7072 (Electronic) 0308-8146 (Linking) |
| Abstract: | "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" |
| Keywords: | Citrus sinensis/*chemistry/metabolism Discriminant Analysis Electronic Nose Gas Chromatography-Mass Spectrometry Italy Principal Component Analysis Solid Phase Microextraction South Africa Spain Volatile Organic Compounds/*analysis/isolation & purificatio; |
| Notes: | "MedlineCentonze, Valentina Lippolis, Vincenzo Cervellieri, Salvatore Damascelli, Anna Casiello, Grazia Pascale, Michelangelo Logrieco, Antonio Francesco Longobardi, Francesco eng England 2018/12/07 Food Chem. 2019 Mar 30; 277:25-30. doi: 10.1016/j.foodchem.2018.10.105. Epub 2018 Oct 23" |
