Unprecedented & powerful tool for extra virgin olive oil traceability

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The extracted DNA is stable overtime and amenable for molecular analyses but there is also the possibility of using the chromatographic fingerprint of the phenolic fraction of extra virgin olive oils coupled to chemometric classification techniques.

Extra virgin olive oil production has a worldwide economic impact. The use of this brand, however, is of great concern to Institutions and private industries because of the increasing number of fraud and adulteration attempts to the market products.

There is a reliable and not expensive method for extracting the DNA from commercial virgin and extra virgin olive oils. The DNA is stable overtime and amenable for molecular analyses; in fact, by carrying out Simple Sequence Repeats (SSRs) markers analysis, we characterize the genetic profile of monovarietal olive oils.

By comparing the oil-derived pattern with that of the corresponding tree we can unambiguously identify four cultivars from Samnium, a region of Southern Italy, and distinguish them from reference and more widely used varieties.

Through a parentage statistical analysis, we also identify the putative pollinators, establishing an unprecedented and powerful tool for olive oil traceability.

In another study, the possibility of using the chromatographic fingerprint of the phenolic fraction of extra virgin olive oils coupled to chemometric classification techniques to trace the origin of extra virgin olive oils with a Protected Denomination of Origin (PDO) was investigated.

In particular, this approach was used to characterize the PDO Sabina (an oil producing area in the center of Italy). Partial Least Squares-Discriminant Analysis (PLS -DA) models were at first built on the HPLC chromatographic profiles recorded at three different wavelengths (254 nm, 280 nm and 340 nm).

Better results were obtained by selecting the most relevant regions of the chromatograms by a combination of backward-interval-PLS and Genetic Algorithms (bi-PLS-GA), especially in the case of the data at 280 nm and 340 nm (about 85% correct classification rate).

Lastly, the use of a mid-level data fusion approach to combine the regions selected at 280 and 340 nm allowed further improving the specificity of the traceability model for PDO Sabina towards other oils.

Identification of the compounds corresponding to regions of the chromatograms selected by bi-PLS-GA using mass spectroscopy suggested that vanillic acid, p-coumaric acid, luteolin, pinoresinol, acetoxypinoresinol, apigenin and metoxyluteolin can play a significant role as traceability markers for the PDO Sabina.

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