Effect of Salting Duration on Lipid Oxidation and the Fatty Acid Content of Dry-Cured Lacon
Bibliographic record
Abstract
We investigated the effects of salting duration (3, 4 or 5 days) on lipid oxidation and the total fatty acid content of muscular fat and subcutaneous fat during the manufacturing of dry-cured lacon, a traditional meat product made in NW Spain from pork foreleg. Two batches of lacon were processed using each salting duration. In each batch, samples were analysed at seven different times throughout the manufacturing process. In each sample, the moisture and NaCl contents, and the peroxide value of the fat and the total fatty acid contents were determined in both the muscular and the subcutaneous fat. Increasing the salting duration significantly increased lipid oxidation (as indicated by peroxide values), in both the muscular and the subcutaneous fat and at all sampling times throughout the manufacturing process. At the end of the ripening stage, the average peroxide values were 7.69, 17.79 and 21.72 meq. of O2/kg of subcutaneous fat and 10.78, 24.96 and 26.48 meq. of O2/kg of muscular fat, in the batches salted for 3, 4 and 5 days, respectively. Salting duration significantly affected the fatty acid content, particularly that of polyunsaturated fatty acids and the linoleic acid within these. The polyunsaturated fatty acid content of lacon pieces salted for 3 days were significantly higher than those of pieces salted for 4 or 5 days, in both the muscular and subcutaneous fat.
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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 | 0.001 |
| 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 | 0.001 |
| 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".