The effects of sow grouping practices on production and mixing aggression
Notice bibliographique
Résumé
As the Canadian swine industry transitions gestation housing from stalls to groups, it is important to understand the impact of different grouping practices on sow productivity and welfare. When sows are housed in groups, a social hierarchy is established through aggressive behaviour which can negatively impact production. Many producers are implementing dynamic groups and early mixing using precision feeding; however, there is potential for greater aggression and the consequences of this practice are not fully known.\nThis study compared the effects of three grouping treatments in gestation on sow productivity and aggression. Treatments included: Control (Con): sows housed in stalls for 35 days after insemination, then moved to static groups; Static (Sta): sows mixed into static groups 1-8 days after insemination; and Dynamic (Dyn): sows mixed into dynamic groups 1-8 days after insemination with monthly mixing (8-10 sows removed and replaced). Mixed parity sows and gilts were housed in groups of 25 per pen in three replicates per treatment. Body weight, body condition score and backfat thickness were recorded once at breeding and again when sows were moved to farrowing. Farrowing rate, litter characteristics and piglet birthweights were recorded. On the day of mixing, sow behaviour was video recorded for measurement of reciprocal and one-sided aggression. Skin lesions and lameness were scored before and after mixing, at ~day 63 of gestation, ~day 91 of gestation, and on the day of moving to farrowing. Hair samples were collected at 7- and 12-weeks post-insemination for cortisol analysis. Statistical analysis was performed in SAS 9.4 using mixed effects models and Chi-square analysis.\nGrouping practice did not have a significant effect on change in body weight, backfat thickness or body condition during gestation. Farrowing rates for Con, Dyn and Sta treatments were 81%, 88% and 62%, respectively (Chi sq p<0.001). There were no significant treatment differences for litter characteristics. At mixing, Sta sows had a higher frequency of reciprocal fighting in the first half hour (Chi sq p<0.001), than did Con or Dyn sows. However, during the 24 hrs following mixing, sows in the Con treatment received more lesions in total than did Sta or Dyn sows (means ±SEM: Con: 11.71 ±0.46; Dyn: 8.69 ±0.40; Sta: 9.09 ±0.41, p<0.01)). Lesion scores decreased significantly over time in all groups. Throughout gestation, Dyn sows had higher lesions overall and a higher incidence of lameness than either Con or Sta sows (p<0.001 and p=0.046, respectively). Although treatment had no effect on hair cortisol concentrations, parity group had a significant effect on concentrations at both timepoints with young sows having the highest concentration and mid parity sows the lowest (p=0.04, p<0.01, respectively).\nIn conclusion, Con and Sta sows appeared to be more aggressive at mixing while aggression in Dynamic groups appeared to be moderated due to the smaller number of unfamiliar sows introduced at each mixing event. Dyn sows had more lesions and increased lameness overall during gestation suggesting increased chronic aggression for dynamic sows, although the results were not severe enough to impact farrowing rate or litter quality. In conclusion, dynamic mixing may serve as a viable housing alternative for pork producers provided that the management strategies are implemented to mitigate the effects of ongoing aggression.
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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 | 0,001 | 0,002 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».