Reliability of the ΔECN42 limit and global method for extra virgin olive oil purity assessment using different analytical approaches. (1st January 2016)

• Record Type: Journal Article
• Authors: Beccaria, Marco; Moret, Erica; Purcaro, Giorgia; Pizzale, Lorena; Cotroneo, Antonella; Dugo, Paola; Mondello, Luigi; Conte, Lanfranco S.
• Is Part Of: Food chemistry. Volume 190(2016)
• Page Start: 216
• Page End: 225
• Publication Date: 2016-01-01
• Subjects: Authenticity -- Olive oil -- Triacyglycerol (TAG) -- Global method -- Delta-ECN42 -- High performance liquid chromatography (HPLC) -- Refractive index detector (RID) -- Mass spectrometry (MS); Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2015.05.075
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Comparison of different HPLC analytical methods for olive oil TAGs analysis. Reliability evaluation of both ΔECN42 and global methods to assess EVOO purity. Discussion on limitations and contradictions of ΔECN42 and global method. Necessity of more efficient and reliable analytical methods and data elaboration. Abstract: Two data elaboration approaches for evaluating olive oils authenticity were compared: (I) determination of the difference between the theoretical and actual amounts of triacylglycerols with partition number 42 (ΔECN42 ⩽ |0.2|); and (II) the global method, which considers also partition numbers 44 and 46 (returning a " correct "/" not correct " result). Analysis of 31 genuine extra virgin olive oil samples was performed using different analytical methods, namely liquid chromatography (LC) coupled with a refractive index detector (RID) and LC coupled with a mass spectrometry (MS), and the results compared. Several false positives were highlighted using the ΔECN42 limit with both instrumental approaches. The global method algorithm returned " correct " results for all the samples analysed (except two that gave no results) with LC–MS; on the other hand, 10 false positives were obtained elaborating data deriving from NARP-LC-RID analysis.