Quantification of the effect of reducing dietary crude protein in broiler chickens on nitrogen flows and litter characteristics by meta-analysis
Bibliographic record
Abstract
In broiler chickens, reducing dietary CP content is an effective strategy to improve the efficiency of dietary nitrogen ( N ) utilisation by broilers while reducing N losses through volatilisation. The purpose of this study was to quantify the effect of lowering dietary CP on N flows (intake, retention, excretion, manure accumulation, and volatilisation). The database included studies that measured N volatilisation using a mass balance approach. A total of nine papers describing 16 trials and 46 observations were found. The effect of CP content on N flow variables was assessed using a linear mixed-effects model with the trial as a random effect. Broilers of the control treatments ingested an average of 4.2 g of N per day and retained an average of 55% of this N. Nitrogen intake that was not retained was excreted (1.9 g/d), and 33% of this excreted N was lost through volatilisation. Reducing dietary CP by 1% point (%-point) decreased N intake by 0.21 g/d ( P < 0.001) without any effect on N retention. Nitrogen excretion and the volatility of excreted N decreased by 0.20 g/d and 4.22%-points, respectively, for each 1%-point reduction in CP content ( P < 0.001). The synergy between the reduced excreted N and its volatility decreased the amount of volatilised N by 0.12 g/d (−23%) for every 1%-point reduction in CP content ( P < 0.001). Reducing CP content also decreased litter mass ( P < 0.05) and increased its DM ( P < 0.01). The data presented show that increasing litter DM content ( P < 0.05) and lowering pH ( P < 0.001) reduces the volatility of excreted nitrogen. The results of this meta-analysis highlight the benefits of this low-CP diet for reducing N losses, and the equations created can be used in future evaluations of the effects of reducing dietary CP content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".