Comparison of Sample Preparation Methods for Multielements Analysis of Olive Oil by ICP-MS.

Elemental analysis of olive oils by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is challenging because of the high organic load in olive oil samples and the low analyte concentrations. However, conflicting operating procedures in the preparation of oils prior to analysis by ICP-MS have been reported to overcome these difficulties. This study compared three methods of inorganic elements' extraction from olive oils: The two commonly used microwave-assisted, acid digestion, and liquid-liquid, ultrasound-assisted extraction methods; and an optimized method: The combined microwave digestion-evaporation. Overall, microwave digestion-based methods did not compare opportunely, and ultrasound-assisted extraction was found to provide the best accord between simplicity of use, detection limits and precision improvement. The detection limits were in the range of 0.3-160 µg·kg-1, 0.012-190 µg·kg-1 and 0.00061-1.5 µg·kg-1, while repeatabilities were in the range of 5-21%, 5.4-99% and 5.1-40% for the microwave digestion, the combined digestion-evaporation and the ultrasound assisted extraction, respectively. The ultrasound-assisted extraction is therefore recommended as a preparation method for olive oils prior to analysis by ICP-MS. The broader range of elements that can be accurately detected is expected to help increase the discriminatory power and performance of geographical traceability models.

Interregional traceability of Tunisian olive oils to the provenance soil by multielemental fingerprinting and chemometrics.

The aim of this study was to prove the usefulness of multielements as provenance markers of olive oils by evaluating their link with soil composition and their discriminatory power. Eleven elements in twenty-one olive oils and their paired soils from four Tunisian regions were characterized. Chemometrics have been implemented for ICP-MS data processing. Principal component analysis identified the predominant geochemical source of the elements in the oils based on their associations according to Goldschmidt's rule. Although a clear correlation was not proven, correspondence was identified between the discriminating elements for both the soils and olive oils, which included Fe, Rb, Mg, and Pb. Linear discriminant analysis achieved classification and prediction rates of 92.1% and 87.3%, respectively. Our study substantiates the validity of multielements as markers of the olive oils' provenance, and that an elemental fingerprinting approach can be successfully applied in the construction of a database of Tunisian olive oils.