Multi-Cumulative Trapping HS-SPME to enhance the volatile profile of extra-virgin olive oil

This work explores the capability of multiple-cumulative trapping (MC) SPME on the characterization of the aroma profiling of olive oils, exploiting the automation capability of a novel headspace autosampler. The theory that underlays this extraction technique is based on the equilibrium among a three-phase system, i.e., sample-headspace-fiber. A compromise between sensitivity and extraction time is usually needed to optimize the sample throughput, mainly when a large number of samples are analyzed, as usually the case in cross-samples studies. Moreover, contrary to what is usually applied, the selection of the sample volume which does not saturate the headspace (i.e. even 10 times lower than the commonly used quantity), is of high relevance in order to maximize the information extractable. In this work, the fingerprinting of olive oil is explored to discriminate among extra virgin, virgin, and lampante oil, a challenging task of interest
for quality and authenticity assessment. The different conditions were compared, considering the general information as pattern analysis, rather than intensity-wise.