Unflappable: Wing flapping of aviary-housed laying hens following spatial restriction
Notice bibliographique
Résumé
Commercial housing systems are becoming more complex to accommodate positive hen behaviors, including wing flapping (WF). Hens need substantial three-dimensional space to flap their wings, and system configurations can influence this behavior. This study examined the timing and frequency of WF among 4 laying hen strains (2 white-feathered and 2 brown-feathered; 576 hens/strain) housed in a commercial-style multi-tiered aviary. Hens were separated by strain into 16 tiered aviary units within 4 rooms (4 units/room, 1 unit/strain/room). Each unit contained a litter-covered floor and a 3-tiered enclosure containing feed, water, perches, and nests. Doors on the bottom tier opened and closed, determining when hens could access litter. Hens were confined within tiered enclosures from 01:00–11:35 daily, providing ∼8.5 h of litter access before lights turned off at 20:00. Ceiling-mounted cameras in each unit captured hens’ behavior on litter. Observers watched 1 day of video footage when hens were 28 weeks old and recorded every stationary WF event. For analysis, time of day (11:35–20:00) was broken into six 85-min blocks of time (A, B, C, D, E, F). A generalized linear mixed model was used to compare counts of WF among the 4 strains. Main effects were the strain and time; random effects were room and unit location within the room. A Spearman rank correlation test was applied to evaluate the relationship between WF counts and density of the birds on the litter. Overall, brown-feathered hens flapped their wings more than white-feathered hens (P < 0.05). More WF events were counted in the morning (time A) compared to evening (time F) (P < 0.05), suggesting hens’ daily confinement within wire enclosures may have increased their motivation to wing flap once they had room to do so. Overall, WF instances were negatively correlated with birds’ density on the litter (r = -0.205; P < 0.001), and a similar pattern was observed within each strain and in F. No correlation was found between WF counts and hens’ density on the litter when hens first gained access to the litter each day (time A). In conclusion, white and brown strains showed different amounts of WF, and time of day and number of hens on the litter influenced how much WF occurred. However, further research is needed to address the impact of intrinsic and extrinsic factors such as age, motivation, litter stocking density, standard management practices like feed distribution, and daily activity patterns. • White laying hens present different wing flapping patterns from brown ones. • Strains of the same feather color also differ in wing flapping pattern. • Wing flapping behavior is influenced by time of day. • Environmental and management factors can affect wing flapping performance.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».