Characterization of Phenolic Compounds and Their Contribution to Sensory Properties of Olive Oil.

Olive oil is not only known for its pungent, bitter, and fruity taste, but also for its health potential, which is often hypothesized to depend on its phenolic compounds. One hundred extra virgin olive oil samples (monocultivaric as well as blends of varieties) were assessed with regard to their sensory properties and phenolic compound composition. Nineteen phenolic compounds have been determined and correlated with sensory data.

Sensory analysis and consumer acceptance of 140 high-quality extra virgin olive oils.

Background: Sensory analysis is a crucial tool for evaluating the quality of extra virgin olive oils. One aim of such an investigation is to verify if the sensory attributes themselves - which are strictly related to volatile and phenolic compounds - may permit the discrimination of high-quality products obtained by olives of different cultivars and/or grown in various regions. Moreover, a crucial topic is to investigate the interdependency between relevant parameters determining consumer acceptance and objective sensory characteristics evaluated by the panel test.

High-performance liquid chromatography-mass spectrometry profiling of phenolic compounds for evaluation of olive oil bitterness and pungency.

Bitterness and pungency are important parameters for olive oil quality. Therefore, two instrumental methods for evaluation of these taste attributes were developed. The first one is based on the photometric measurement of total phenolic compounds content, whereas the second one is based on the semiquantitative evaluation of hydrophilic compounds by high-performance liquid chromatography-mass spectrometry (HPLC-MS).

Quality evaluation of olive oil by statistical analysis of multicomponent stable isotope dilution assay data of aroma active compounds.

An instrumental method for the evaluation of olive oil quality was developed. Twenty-one relevant aroma active compounds were quantified in 95 olive oil samples of different quality by headspace solid phase microextraction (HS-SPME) and dynamic headspace coupled to GC-MS. On the basis of these stable isotope dilution assay results, statistical evaluation by partial least-squares discriminant analysis (PLS-DA) was performed.