Effects of Dietary Conjugated Linoleic Acid on Broiler Performance and Carcass Characteristics
Bibliographic record
Abstract
The effects of three levels of conjugated linoleic acid dietary inclusion on the carcass characteristics and performance of broilers were evaluated. A total of 405 chickens were raised from 1 until 42 days of age, housed in a room with water and food ad libitum. The experimental design was completely randomized, with three treatments (0.0, 0.5 and 1% CLA) and nine replications (pen) to performance analysis, 18 replications (two birds per pen) to carcass composition, and five replications (left legs) to lipid profile. Performance was determined weekly and after 42 days, 18 birds per treatment were slaughtered to quantify breast and leg yield. Protein and fat was quantified in the leg and breast, as well as the detailed lipid profile of the leg. Data were analyzed by ANOVA and means compared by LS means. From 1 to 21 days chickens with 0% supplementation of CLA performed better compared to those receiving 0.5 and 1% CLA (P < 0.05), however, these differences were no longer significant from 21 to 42 days or for the overall study period (P > 0.05). Conjugated linoleic acid inclusion did not influence leg, breast and carcass yield, and leg and breast content of protein and fat. Both levels of CLA changed the leg lipid profile: there was an increased accumulation of CLA in meat, increased levels of saturated fatty acids and reduction of polyunsaturated fatty acids. Conjugated linoleic acid supplementation increased n-6:n-3 ratio. CLA supplementation in broiler feed is effective to produce meat enriched with its isomers and change lipid profile.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".