Maternal age and maternal environment affect egg composition, yolk testosterone, offspring growth and behaviour in laying hens
Bibliographic record
Abstract
Maternal effects have been reported to alter offspring phenotype in laying hens. In this study, we investigated the effects of maternal environment and maternal age on egg traits and offspring development and behaviour. For this, we ran two experiments. First (E1), commercial hybrid hens were reared either in aviary or barren brooding cages, then housed in aviary, conventional cages or furnished (enriched) cages, thus forming different maternal housing treatments. Hens from each treatment were inseminated at three ages, and measures of egg composition, yolk testosterone concentration and offspring's development, anxiety and fearfulness were assessed. In experiment 2 (E2), maternal age effects on offspring's growth and behaviour were further investigated using fertile eggs from commercial breeder flocks at three different ages. Results from E1 showed that Old hens laid heavier eggs with less yolk testosterone and produced offspring with fewer indicators of anxiety and fearfulness. Maternal rearing and housing affected egg traits, offspring weight and behaviour, but not in a consistent way. Effects of maternal age were not replicated in E2, possibly due to differences in management or higher tolerance to maternal effects in commercial breeders. Overall, our research confirms that maternal age and maternal environment affects egg composition, with maternal age specifically affecting yolk testosterone concentration, which may mediate physical and behavioural effects in offspring.
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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 | 0.000 | 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) | 0.001 | 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".