Genetics of phytate phosphorus bioavailability: heritability and genetic correlations with growth and feed utilization traits in a randombred chicken population
Bibliographic record
Abstract
The current study was undertaken to estimate variance components for phytate P bioavailability (PBA) and the genetic correlations among PBA with growth and feed utilization (or intake) traits in an unselected random mating chicken population. Pedigreed data from 901 Athens-Canadian randombred chickens hatched from 26 sires, 71 dams, and 105 grandparents were used for estimation of genetic parameters. Birds were individually housed in metabolic cages at 4 wk of age and fed a 0.35% P diet. After 3 d of acclimatization, excreta produced for 3 consecutive d were collected and feed consumed (FC) was measured. Individual 4-wk BW and BW gain (BWG) during the 3-d excreta collection period were also measured. Feed conversion ratios (FCR) were calculated. Phytate P bioavailability was estimated from the disappearance of phytate during the passage of feed through the gastrointestinal tract. The restricted maximum likelihood method with the average information matrix algorithm was used for the estimation of variance components. The heritability estimate for PBA was about 0.10. Genetic correlations between PBA and BW, BWG, and FC were moderate and negative, indicating that improving PBA utilization would moderately affect growth. The genetic correlation between PBA and FCR was negligible and suggested that selection for PBA will not adversely affect FCR. The economic implications of genetically modifying poultry to improving phytate P utilization and the subsequent elimination or reduction of the amount of phytase used in poultry diets are yet to be determined.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".