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.
Project details
Unibo Team Leader: Giuseppina Schiavo
Unibo involved Department/s:
Dipartimento di Scienze e Tecnologie Agro-Alimentari
Coordinator:
Università degli Studi di PADOVA(Italy)
Total Unibo Contribution: Euro (EUR) 78.130,00
Project Duration in months: 24
Start Date:
12/10/2023
End Date:
28/02/2026
