Preweaning mortality in group-housed lactating sows: Hormonal differences between high risk and low risk sows
Notice bibliographique
Résumé
This study used an endocrinological approach to explain the differences between sows that have higher vs. lower preweaning mortality in a group-farrowing system. The association between sows that had 2 or more piglets die within the first 72 h postfarrowing (high risk) or sows that had 1 or no piglets die within the first 72 h postfarrowing (low risk) with changes in serum hormone concentrations was investigated. Multiparous sows (n = 63; parity 2 to 7) from 4 contemporary breeding groups, each mated within a week, were used. Sows were housed in a group-farrowing system where 8 sows farrowed in individual pens and shared a communal feeding and dunging area in each room. Reproductive performance, including total born, born alive, and stillborn per litter, individual weight of piglets at birth and weaning (at 5 wk postfarrowing), litter size at weaning, preweaning mortality of piglets, and sow BW before farrowing and after weaning, were recorded for all sows. Of these sows, 14 sows from 2 breeding groups were selected randomly for blood sampling through an indwelling ear vein catheter. A blood sample was collected daily from each sow 2 d prefarrowing through 2 d postfarrowing. Serum samples were analyzed for prolactin, oxytocin, cortisol, and urocortin concentrations using RIA. Among the 14 sows, 7 sows lost 2 or more piglets during the first 72 h after farrowing and were classified as high risk sows, and the other 7 sows lost 0 or 1 piglet during the same period and were classified as low risk sows. Catheters in 11 sows (5 high risk sows and 6 low risk sows) remained functional for the entire sampling period. Results indicate that high risk sows farrowed larger litters (live born = 13.8 ± 0.50 vs. 11.3 ± 0.48 piglets; P = 0.03) with lighter piglets (1.4 ± 0.04 vs. 1.7 ± 0.05 kg; P < 0.001) compared with low risk sows. In addition, high risk sows had greater oxytocin concentrations (0.09 vs. 0.07 ng/mL; SE = 0.02, P = 0.01), which might be associated with larger litters farrowed, compared with low risk sows. There were no differences between high risk and low risk sows (P > 0.30) in terms of serum prolactin, cortisol, or urocortin concentrations. These results suggest that litter size and birth weight of piglets played an important role in preweaning mortality of piglets and hormone concentrations in sows were not associated with piglet mortality in the group-farrowing system used.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 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 | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».