Danilo CorradiniItaly

Plant secondary metabolites are not only an important part of plant defense system against pathogenic attacks and environmental stresses, but also a useful array of natural products with remarkable biological activities. Most of them are the therapeutic agents occurring in medicinal plants and play important roles in disease prevention and health-promoting effects of edible plants and plant-derived food products and dietary supplements. Moreover, a variety of plant secondary metabolites confer specific sensory characteristics to plant-based foods, processed or not, whose botanical and geographical origin may be related to their occurrence and amount. Thus, these compounds are also potential chemical markers for the evaluation of botanical and geographical origin of plant-derived food products and dietary supplements. This communication describes the development of computer-assisted RP-HPLC methods for the separation, identification and quantification of phenolic compounds, which are a large class of plant secondary metabolites with health-promoting properties comprising a great number of heterogeneous structures. The study has been conducted by a Design of Experiments (DoE) approach that allows the simultaneous optimization of gradient time (tG), column temperature (T) and binary or ternary mobile phase composition on the basis of the retention times and peak areas of selected phenolic compounds, obtained by a restricted number of experiments. The resulting RP-HPLC methods have been used to investigate the occurrence and content of phenolic compounds in leaves and fruits of olive trees (Olea europaea), in monovarietal extra virgin olive oil of different cultivar and geographical origin, and in olive mill waste water produced by processing the same selected batches of olive fruits by a laboratory olive oil press machine. The different phenolic compound profiles and content determined in samples differing for botanical and geographical origin and/or for the technological transformation process are illustrated and discussed.

Acknowledgements:
This work was supported by MSCA-RISE Action of the H2020 Programme, Project 734899 - Olive-Net.