On The Possibility to Trace Frozen Curd in Buffalo Mozzarella Cheese
Bibliographic record
Abstract
The manufacturing of Buffalo Mozzarella PDO (Protected Designation of Origin) cheese requires the exclusive use of fresh buffalo milk, which must be transformed into cheese within 60 hours after milking. The limited availability of buffalo milk and simultaneous increase in Mozzarella demand during the summer cause producers to use frozen intermediates (milk and/or curd) in the cheese-making process. These practices are not allowed. Few data are available in the literature about the effects of freezing on buffalo milk and curd. Recent studies demonstrated that the use of frozen buffalo milk can be detected in mozzarella cheese based on the increase in casein fragment γ4-CN. This work aims to verify the possibility of tracing the presence of frozen curd in Buffalo Mozzarella PDO cheese. The electrophoresis technique was used to reveal the presence of γ4-CN. Equivalent concentrations of this fragment were found in fresh and frozen curd that were stored for 9 months. Our results suggest that γ4-CN cannot be used to discriminate fresh PDO Mozzarella and Mozzarella cheese produced from frozen curd. A second objective of the work was to evaluate the effects of freezing on curd lipids. In particular, the fatty acid and mono-diglyceride profiles were evaluated. Significant differences were found in the amounts of 1,2-Dipalmitin and 1,3-Diolein between fresh curd and curd that was stored for 9 months at freezing temperatures. Although some significant differences were found in the mono-diglyceride profiles, no objective marker that can distinguish between fresh and frozen products is currently available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".