High eggshell temperatures during incubation decrease growth performance and increase the incidence of ascites in broiler chickens
Bibliographic record
Abstract
High eggshell temperatures (EST; ≥38.9°C) during the second half of incubation are known to decrease the body and organ development of broiler hatchlings. In particular, relative heart weights are decreased by a high EST, and this may increase the incidence of metabolic disorders that are associated with cardiovascular development, such as ascites. The current study investigated the effects of a high EST on chick quality, subsequent performance, and the incidence of ascites later in life. Eggs were incubated at a normal (37.8°C) or high (38.9°C) EST from d 7 of incubation onward. After hatching, the chickens were housed per EST in pens, and a normal or cold temperature schedule was applied during the grow-out period. Hatchability, hatchling quality, BW, feed conversion ratio, total mortality, mortality associated with ascites, slaughter characteristics, and ascites susceptibility at 6 wk of age were evaluated. Except for total ventricle weight, no interaction was found between EST and the grow-out temperature. Hatchability was comparable between the EST treatments, but the percentage of second-grade chickens was 0.7% higher at the high EST. Yolk-free body mass was 3.0 g lower, and heart weights were 26% lower at hatch in the high compared with the normal EST treatment. Body weight continued to be less during the grow-out period after the high EST incubation. However, breast meat yield was 1.0% higher in the high than in the normal EST. Feed conversion ratio did not differ between EST treatments. Total mortality was 4.1% higher and mortality associated with ascites was 3.8% higher in the high compared with the normal EST treatment. The ratio between the right and total ventricle was 1.1% higher in the high compared with the normal EST treatment at slaughter age. In conclusion, a high EST from d 7 of incubation onward decreased hatchling quality and growth performance, but increased breast meat yield. Furthermore, high EST incubation increased the incidence of ascites, which may be related to the reduced heart development at hatch.
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 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) | 0.000 | 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 | 0.001 |
| 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".