Seminario

High performing VOC analysis to improve the horticultural production chain

Seminario rivolto agli studenti del corso di laurea magistrale in Agrifoodi Innovation Management
9 maggio 2022
Polo di Mesiano - Via Mesiano 77, Trento
Aula 2C
Organizzato da: 
prof. Eugenio Aprea
Destinatari: 
Comunità studentesca UniTrento
Partecipazione: 
Ingresso libero
Referente: 
prof. Eugenio Aprea
Speaker: 
Brian Farneti - Berries genetics and breeding unit, Research and Innovation Centre

Abstract

The extreme complexity of food aroma and flavour is a challenging issue for any existing analytical technology. The rapid development of mass spectrometry (MS) application in metabolomic studies had a significant impact in the field of VOC analysis. The progress of MS techniques is mostly focused on instrumental improvements of mass resolution, mass accuracy, sensitivity, and enhanced reproducibility. Direct injection mass spectrometric techniques, such as PTR-ToF-MS (Proton Transfer Reaction – Time of Flight- Mass Spectrometry) and SIFT-MS (Selected Ion Flow Tube – Mass Spectrometry), have opened new possibilities for food aroma analysis by decreasing the time needed for sample preparation and analysis, and by providing the possibility of non-destructive, real time and high-throughput volatilome analysis. 
Tailored pre- and post-harvest studies confirmed the potentials of PTR-ToF-MS application into the whole agro-food production chain, from breeding to consumers. These studies allowed to estimate the interaction between genetic variability, ripening stages and storage condition on the perceived quality of several fruit species. Another important attainment was the development of putative VOC biomarkers linked with fruit spoilage caused, for instance, by the occurrence of postharvest disorders or by fresh-cut processed deterioration.
This seminar aims at reviewing several prototypical analytical approaches, based on chemical ionization mass spectrometry, suitable to address the aroma complexity of agro-food products in different situations:

  • non-destructive VOC assessment; 

  • high-throughput automated headspace analysis;

  • dynamic destructive analysis;

  • real-time process monitoring.