In inland areas of Portugal and some regions of the Mediterranean basin, olive production
is based on traditional olive groves, with low intensification, local cultivars, aged plants, and centenarian
trees. These plants play a key role in the ecosystem, contributing to carbon sequestration and
possessing a high genetic diversity, particularly important for selecting cultivars more resistant to
climatic changes. Appreciation of the value of this genetic diversity implies genetic, morphological,
and physicochemical characterization of centenarian trees, which is expensive and time-consuming.
Sensory evaluation is also of utmost importance. Thus, in this study, centenarian olive trees were
selected in the Côa Valley region, a UNESCO World Heritage site. The descriptive sensory profile of
their extracted olive oils was established and used to cluster the oils, using hierarchical clustering
analysis, and consequently the olive trees, into five groups with similar intensities of perceived
olfactory–gustatory attributes. Each cluster revealed olive oils with unique sensory patterns, presumably
due to similarities of the olive trees, confirming the potential of the proposed screening
approach. The identification of sensorially homogeneous oil-tree groups would reduce the number of
specimens needed for subsequent morphological, genetic, and chemical characterization, allowing a
cost-effective and robust future evaluation procedure.
The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support from national funds FCT/MCTES to CIMO (UIDB/00690/2020) and SusTEC (LA/P/0007/2020). This work was also supported by the FCT project OLIVECOA-Centenarian olive trees of Coa Valley region: rediscovering the past to valorize the future, ref. COA/BRB/0035/2019. Nuno Rodrigues was funded by FCT-Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract.
