Nutritional Impact of Canola Meal on Performance, Blood Constituents and Immune Response of Broilers
Bibliographic record
Abstract
This study was conducted to evaluate the effects of replacing soybean meal (SBM) protein with canola meal (CM) protein on productive performance, nutrient digestibility, immune response, lymphoid organs, blood parameters, carcass fatty acids and cecum microbiota of broilers. A total of 160 one d-old Arbor Acres broiler chicks were randomly allocated to 4 dietary treatments of 5 replicates, where, CM protein replaced SBM protein at 0, 30, 60, and 90% for a 39 days feeding trial. The results showed no significant differences in productive performance parameters among control, 30% and 60% treatment groups, while, at 90% replacement level, all values decreased (P < 0.0001) all over the experimental period. The 90% replacement group showed depression of crude protein (P < 0.001) and crude fiber (P < 0.001) digestibility and spleen relative weight (P = 0.0386) with increase of thymus (P = 0.0555), bursa (P = 0.0334) and thyroid relative weight (P = 0.0276) as well as thyroid hormones (P = 0.0034, 0339) for T3, T4, respectively, while, there were no significant differences among control, 30% and 60% treatment groups for those criteria. However, CM levels had no effect on serum haemagglutination inhibition (HI) titer against Newcastle disease. CM significantly decreased serum cholesterol content (P = 0.0002) while increased HDL (P = 0.0532), compared to the control. CM levels showed an increase in carcass meat content of unsaturated fatty acids content (P < 0.0001) as the replacement level gradually increased. Erucic acid did not detected in carcass. All CM levels decreased cecum content of E. coli (P = 0.0051) while increased that of Lactobacillus (P = 4094). Conclusively, CM can be used safely in broiler diet to replace up to 60% of SBM protein without negative effects on growth and immune response of broilers.
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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) | 0.001 | 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".