Effect of Nitrite Substitution with Olive Leaves Extract on Color and Sensory Properties of Beef Mortadella
Bibliographic record
Abstract
Six mortadella treatments were prepared for studying the effect of olive leaf extract (OLE) at a level of 240 mg OLE/100 g meat as nitrite alternative on the color and sensory characteristics. These treatments were: control with the addition of 120 ppm sodium nitrite only, and the second one with the addition of 240 mg OLE/100 g meat but without the addition of sodium nitrite as a negative control, the other four treatments were combination of 240 mg OLE/100 g meat with 80, 60, 40 and 20 ppm sodium nitrite, respectively. All samples were stored at 5 °C for 1, 3, 6, 9, and 12 weeks. There were no significance differences (P > 0.05) between all mortadella treatments regarding their proximate parameters. Hunter lightness (L), redness (a), and yellowness (b) color, and sensory attributes including the appearance, color, tenderness, juiciness, flavor, and overall acceptability showed that 80 and 60 ppm nitrite in combination with OLE at 240 mg/100 g meat had the best results in comparison with the other four treatments indicating an additive combined effect of the OLE with nitrite that enhanced mortadella characteristics. These results revealed the ability to substitute 50% of the used nitrite in mortadella stored at 5 °C when using combinations of 60 ppm nitrite with 240 mg OLE/100 g meat.
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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 | 0.000 | 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) | 0.002 | 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".