Abstract
The project aims to develop an automatic quality assessment system for PDO dry-cured ham using 2D-3D imaging and hyperspectral analysis combined with machine learning. The goal is to classify fresh hams for visual defects and predict traits like fat thickness and weight loss during curing. It also aims to identify genes associated with meat quality through RNA sequencing and genotyping. The system will offer the ham industry a tool for monitoring the process and integrating new knowledge into genetic evaluations.
Dettagli del progetto
Responsabile scientifico: Giuseppina Schiavo
Strutture Unibo coinvolte:
Dipartimento di Scienze e Tecnologie Agro-Alimentari
Coordinatore:
ALMA MATER STUDIORUM - Università di Bologna(Italy)
Contributo totale di progetto: Euro (EUR) 188.683,00
Contributo totale Unibo: Euro (EUR) 104.425,00
Durata del progetto in mesi: 24
Data di inizio
30/11/2023
Data di fine:
28/01/2026
