Fatty acid profile and chemical composition of meat from Nellore steers finished on pasture with different amounts of supplementation
Bibliographic record
Abstract
The use of supplements to feed grazing ruminants may improve the productivity and profitability of beef cattle productive systems. This study aimed to evaluate the effect of different supplementation amounts on the meat quality of Nellore steers finished on pasture. A total of 40 steers were maintained on Brachiaria brizantha ‘Marandu’ pasture and finished on different concentrate supplementation amounts: 0%, 0.3%, 0.6%, and 0.9% of body weight (BW). There was no effect (P > 0.10) of supplementation on 14:0, 14:1 n-5, 15:0, 15:1 n-6, 16:1 n-10, 16:1 n-9, 16:1 n-7, 18:1 c-9, 18:1 t-9, 18:2 n-6, conjugated linoleic acid, 20:4 n-6, 22:0 and 22:5 n-3. However, the 17:1 n-10 decreased linearly (P < 0.01), whereas 18:0 increased linearly (P < 0.01) when supplementation was added. There was a quadratic effect (P < 0.10) for 16:0 and 18:1 t-11, as well as for 18:3 n-6. The total concentration of n-3 was linearly reduced, whereas the n-6/n-3 ratio was linearly increased. The use of concentrate supplements for Nellore steers finished on pasture, at amounts up to 0.9% of BW, does not improve the unsaturated fatty acids content. In contrast, the supplementation increases the content of saturated fatty acids in meat of steers.
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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 | 0.000 |
| 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".