Effects of dietary crude protein levels on ammonia emission, litter and manure composition, N losses, and water intake in broiler breeders
Bibliographic record
Abstract
This study determined the effects of different dietary crude protein (CP) levels on ammonia emission (NH3), litter and manure composition, nitrogen (N) losses, and water intake in broiler breeders. A total of 480 females and 64 males (Ross 308) 20 wk of age were randomly allotted to 2 dietary treatments with 8 replicates of 30 females and 4 males per replicate. Birds were fed either high CP (CPh) or low CP diets (CPl) supplemented with free amino acids (AA). Both diets consisted of 3 sub-diets; 1 for each phase of the laying period. Diets were formulated to be iso-caloric and calculated CP content of the CPl diets was 15 g/kg lower than the CPh diets (Breeder 1 (23 to 34 wk): 135 vs. 150, Breeder 2 (35 to 46 wk): 125 vs. 140 and Breeder 3 (47 to 60 wk of age): 115 vs. 130 g/kg, respectively). Pens consisted of an elevated slatted floor (25% of the floor surface) and a litter floor. Water and feed intake were recorded daily. Litter (floor) and manure (below slatted floor) composition and ammonia concentration were measured at 34, 44, and 54 wk of age. Ammonia concentration was measured using a flux chamber on top of the litter or manure. Estimated N losses were calculated. Dietary protein level did not affect water intake and dry matter (DM) content of the litter or manure. Compared to birds fed the CPh diets, the litter and manure samples of broiler breeders fed the CPl had 8% lower total-N and 13% lower ammonia-N content resulting in a 9% lower ammonia concentration, 9% lower ammonia emission, and 11% lower total-N losses. In conclusion, this study shows that reducing CP level in the diet of broiler breeders reduces ammonia emission and total N-losses from litter and manure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".