Texture and Chemistry of Iranian White Cheese as Influenced by Brine Treatments
Bibliographic record
Abstract
The effect of different brine concentrations, pH of brine, and type of the used acid in brine on chemistry, element content, a w (water activity), texture and microstructure of Iranian white cheese was studied. A batch of Iranian white cheese was produced, divided into 8 blocks, and immersed in 8 brine treatments i.e., L1(Cheese ripened at 16% brine concentration with pH equal to 5 and lactic acid for pH adjusting), L2 (Cheese ripened at 10% brine concentration with pH equal to 5 and lactic acid for pH adjusting), L3 (Cheese ripened at 10% brine concentration with pH equal to 4.3 and lactic acid for pH adjusting), L4 (Cheese ripened at 10% brine concentration with pH equal to 3.6 and lactic acid for pH adjusting), C1 (Cheese ripened at 16% brine concentration with pH equal to 5 and citric acid for pH adjusting, C2 (Cheese ripened at 10% brine concentration with pH equal to 5 and citric acid for pH adjusting), C3 (Cheese ripened at 10% brine concentration with pH equal to 4.3 and citric acid for pH adjusting), and C4 (Cheese ripened at 10% brine concentration with pH equal to 3.6 and citric acid for pH adjusting). Cheese samples were analyzed with respect to chemical characteristics, rheological parameters and microstructure. Increasing the brine concentration increased the instrumental hardness parameters (i.e., fracture stress, elastic modulus, and storage modulus). pH and type of the used acid in brine had no significant effect on these parameters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".