Effects of Dietary Crude Protein on Performance and Nitrogen Economy of Broilers
Bibliographic record
Abstract
This study assessed the effects of dietary crude protein on performance and nitrogen economy of broilers. Chicks were allotted to 22, 20, 18 and 16% crude protein corn-soy diets in a completely randomized design for forty-two days. Several essential amino acids were observed to be deficient compared to recommendations for broiler chicks as the dietary crude protein level reduced. Feed intake, weight gain, feed to gain ratio, faecal nitrogen, nitrogen retention, anthropogenic potential and dressing percentage were influenced (P < 0.05) by the dietary treatments. However, mortality was not significantly different (P > 0.05). Feed intake, weight gain, nitrogen intake and output were significantly (P < 0.05) depressed as the CP level reduced. However, the best (P < 0.05) nitrogen retention and percentage faecal nitrogen was recorded for broilers fed 20% crude protein diet. Serum total protein, albumin, uric acid, creatinine and glucose were affected (P < 0.05) across treatments. It was concluded that there is a limit to which dietary crude protein of broilers could be reduced without any detrimental effects on the performance and nitrogen economy of the birds, even when the requirements for methionine and lysine has been met, as several other amino acids could be limiting. Consequently, to achieve significant improvement in nitrogen economy and reduction in amount of faecal nitrogen, 20% crude protein diets could be fed to broilers. However, there may be need to further manipulate the amino acid profile of the diet so as to improve its performance to be at par with higher crude protein diets.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".