Partitioning of Retained Energy in Broilers and Birds with Intermediate Growth Rate
Bibliographic record
Abstract
An experiment was conducted to study energy retained (TER) as fat (TERF) and protein (TERP) in 3 strains of birds with different growth rate; commercial broilers, Barred Plymouth Rock, and Leghorns. Birds were fed ad libitum a diet providing 3,100 kcal of AMEn/kg and 20% CP from 0 to 42 d. Body composition, TER, TERF, and TERP were determined at 0, 7, 10, 15, 19, 23, 28, 33, 37, and 42 d of age. The TER, TERF, and TERP were derived from whole body analyses. Linear and nonlinear models (quadratic, allometric, and Gompertz equation) were used as a means to characterize observed patterns of energy deposition. The TER, TERF, and TERP increased quadratically (P < 0.001) over time in all 3 strains of birds. Over 42 d, broilers deposited a constant proportion (50%) of body energy as fat and protein (P < 0.001). When applying the Gompertz equation to relate empty BW (EBW) to time, the estimated value for EBW at maturity of the broilers was unrealistically high (11.1 kg) and estimated poorly (SE 5.5 kg). Quadratic equations may be used as an alternative for Gompertz equations to represent growth of EBW, TER, TERF, or TERP vs. time in chickens between 0 and 42 d of age. Within the BW ranges that were evaluated in this study, allometric functions or Gompertz equations can be used to relate TERF and TERP to EBW, but model parameters differ between bird strains. Based on the Gompertz equation and in broilers, the maximum rate of TERF and TERP was reached at 1.16 and 1.22 kg of EBW, respectively, and then declines slowly as BW increases. Quantifying and partitioning TER as TERF and TERP as major components of ME requirements can be used to establish models that have economic consequences to the broiler industry.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".