Image-Based Machine Learning for Predicting Acceptability Limits in Frozen Pizza Shelf Life
of 0.68 and an RMSE of 12.8, while the classifier attained an accuracy of 88.2% and an AUC of 0.93. The resulting framework enables early, non-invasive estimation of product acceptability and shows strong potential for practical application in shelf life studies within the frozen food industry.
Authors
- Sylvio Barbon (ORCID: https://orcid.org/0000-0002-4988-0702)
- Maria Cristina Nicoli (ORCID: https://orcid.org/0000-0001-8413-8549)
- Giulia Varutti (ORCID: https://orcid.org/0009-0004-0119-0122)
Institutions
- University of Udine (IT)
- University of Trieste (IT)
Publication Details
- Journal
- Foods
- Published
- 2026-04-13
- DOI
- https://doi.org/10.3390/foods15081348
- Primary Topic
- Sensory Analysis and Statistical Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00