Clustering of Italian Monovarietal Extra Virgin Olive Oil through Statistical Analysis of Sensory and Chemical Data for its Valorization

Monovarietal extra virgin olive oil (MEVOO) is a niche product whose production has been constantly increasing in the last decades. MEVOOs of different cultivars are characterized by peculiar sensory attributes, which appeal to specific consumer segments. However, consumers’ choices are still mainly driven by the country of origin of an oil rather than by its botanical origin, as many consumers do not have adequate tools to appreciate the peculiar sensory features of oils from different cultivars. This happens also because MEVOO’s characteristics are often not well-defined, and consumer information is lacking on the topic. MEVOOs of different cultivars are also differentiated by chemical profiles: phenolic compounds, terpenes and LOX pathway derived VOCs are the molecules more capable of differentiating MEVOOs [1]. The aim of this research was to divide MEVOOs into clusters of cultivars mainly based on their sensory features, while searching for correlation with chemical data. Approximately 300 samples from 14 of the main Italian cultivars, collected over 4 harvesting seasons (2020-2023) were sensorially evaluated by a professional panel using an innovative profile sheet focused on the different nuances of positive attributes, and analyzed via HPLC-DAD (phenolic fraction) and HS-SPME-GC-MS (terpene and volatile fractions) [1,2]. The analysis of sensory data with GA-LDA-HCA allowed the cultivars to be grouped into three distinct clusters, which were validated using chemical data (accuracy ≈ 96%). The most significant sensory and chemical parameters that characterized each cluster were individuated and correlated when possible. This approach can be useful for MEVOOs’ valorization in terms of consumer knowledge and acceptability, as well as to create different segments of MEVOO and different concourse classes, characterized by specific sensory and chemical profiles