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UCO Revolutionizes Olive Oil Analysis with Predictive Method

Researchers at the University of Córdoba develop a technique to predict EVOO quality directly from the olive, prior to extraction.

Image of green olives on a branch with a blurred laboratory in the background.
IA

Image of green olives on a branch with a blurred laboratory in the background.

Researchers from the Analytical Chemistry Department at the University of Córdoba have developed a pioneering method to predict the quality of extra virgin olive oil directly from the olive, before extraction, offering speed and precision.

Virgin olive oil, a fundamental pillar of the Mediterranean diet, is valued for its health benefits. Its quality is determined by three key chemical families: fatty acids, phenols, and volatile compounds. These elements are responsible for the oil's healthy value, its organoleptic characteristics, such as fruity aroma, and its oxidative stability, which defines how long it remains in optimal condition.
Traditionally, to determine the presence of these compounds in an EVOO, it was necessary to first extract the oil and then perform laboratory analyses. However, a team from the University of Córdoba, composed of Feliciano Priego, Enrique Cabanas, Carlos Ledesma, and Mónica Calderón, has devised a procedure that eliminates this need, allowing the oil's composition to be known directly from the olive.

"We sought to get ahead, trying to assess in the fruit what we might find later in the oil. Without the need to mill kilos of olives, we predict the composition that oil would obtain."

Feliciano Priego · Head of the FQM-227 group
The method, described as “simple” and “fast” by Carlos Ledesma, a Ramón y Cajal researcher at the UCO, involves removing the olive pit and inserting a solid-phase microextraction fiber to absorb volatile compounds. Subsequently, with the extracted material, the phenolic profile and fatty acids are determined. The results have shown 100% accuracy, identifying 79 metabolites, including 13 fatty acids, 21 phenols, and 45 volatile compounds.
Mónica Calderón was responsible for developing the predictive panels to classify the oils, a tool that combines different compounds and cutoff points. The robustness of the method was validated by comparing results obtained from the olive with those from already extracted oil. This advancement not only streamlines the process but also allows producers to select the optimal harvest time to achieve the desired chemical profile, whether for its sensory value or the presence of specific antioxidants like oleocanthal.
This innovative development, which utilized eight olive varieties from the UCO World Olive Germplasm Bank, opens new avenues for exploring other varieties and applying the technique to other fruits. The team is already considering future challenges, such as prolonged maturation studies and the possibility of taking the method directly to the field for in situ analysis.