Differentiation of Italian extra virgin olive oils by rapid evaporative ionization mass spectrometry. (March 2021)

• Record Type: Journal Article
• Authors: Mangraviti, Domenica; Rigano, Francesca; Arigò, Adriana; Dugo, Paola; Mondello, Luigi
• Is Part Of: Lebensmittel-Wissenschaft + Technologie =. Volume 138(2021)
• Publication Date: 2021-03
• Subjects: Food authenticity -- PDO trademark -- Monocultivar oil -- Iknife -- Spectral database; Food industry and trade -- Periodicals; Food -- Composition -- Periodicals; Microbiology -- Periodicals; Nutrition -- Periodicals; 664.005
• DOI: 10.1016/j.lwt.2020.110715
• Languages: English
• ISSNs: 0023-6438

Abstract

Abstract: The present work aims to differentiate Italian extra virgin olive oils through the analysis of about 100 samples for the building of a spectral database useful for the comparison beetwen top-quality oils. High-quality oils belonging to two different harvest years and coming from different Italian regions, labelled as PDO (Protected Denomination of Origin) or obtained from a single variety of olives (monocultivar), were available. Rapid Evaporative Ionization Mass Spectrometry, in combination with a monopolar handpiece as sampling device was explored for the first time on liquid and poorly conductive samples. Multivariate analyses were applied to build different chemometric models. The monocultivar oils gave positive feedback, leading to the reliable identification of each cultivar. The recognition of PDO oils resulted more challenging (failure percentage > 5%), probably due to the major intra-class variability, since oils labelled with the same PDO trademark often are produced from different cultivar in different percentages. Highlights: A database of Italian extra virgin olive oils was built through the iknife technique. Statistical models allowed better discrimination according to olive varieties than PDO mark. An emulsion with a saline solution enhanced sample conductivity and ionization. Highly informative REIMS spectra enabled a quali-quantitative comparison of oils. A prediction rate higher than 90% was achieved and no false positive were obtained.