Broiler performance, body weight variance, feed and water intake, and carcass quality at different stocking densities
Bibliographic record
Abstract
The effects of four stocking and water nipple densities on broiler performance and carcass traits were measured in two trials. The stocking densities of 23.8, 17.9, 14.3, and 11.9 birds/m2 corresponded to 260, 195, 156, and 130 birds per pen, respectively. The water nipple densities were 5, 10, 15, and 20 birds per water nipple. Birds in Trial 1 were processed at Day 39 and those in Trial 2 were processed at Day 42. Water and feed were provided ad libitum and light was provided 23 h/ d. Water nipple density had no effect on broiler performance or carcass quality. Birds grown at 23.8 birds/m2 had lower BW (1,898 g) and carcass weights (1,334 g), whereas birds grown at 14.3 birds/m2 had the highest BW (1,985 g) and carcass weights (1,432 g). Although the treatment with 23.8 birds/m2 gave the lowest BW, the yield of broilers per unit of floor space was highest (46.0 kg/m2). The coefficient of variation for BW was higher in the treatment with 11.9 birds/m2 (15.3 %) than in the other treatments (13.0%). The birds in the treatment with 11.9 birds/m2 consumed the least feed (2,993 g/bird) and those in the 14.3 birds/m2 treatment consumed the most feed (3,183 g/bird). The amount of water consumed and the water to feed ratio was highest in the 23.8 birds/m2 treatment (5,546 mL/bird and 1.85 mL/g, respectively). Stocking density had no effect on mortality, breast yield, carcass grading, incidence of scratches, or carcass quality. It was concluded high yield per unit area with good carcass quality could be achieved when ventilation rate and air circulation were adequate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".