Prevalence of welfare outcomes in the weaner and finisher stages of the production cycle on 31 Irish pig farms
Notice bibliographique
Résumé
BACKGROUND: Knowledge on the most prevalent welfare problems for pigs in different production stages is required to improve herd management plans. Thirty-one farrow-to-finish pig farms were visited between July and November 2015 to assess the welfare of pigs using the multicriteria approach of the Welfare Quality® protocol. On each farm, 6 pens were selected using proportionate stratified sampling in the first weaner (S1, 4 to 8 wks), second weaner (S2, 8 to 13 wks) and finisher stage (S3, 13 to 23 wks), excluding hospital pens. Each pen was observed for 10 min and the number of pigs affected by different welfare outcomes was recorded. The percentage of pigs affected was calculated and ranked to identify the most prevalent outcomes within each production stage. Differences between production stages were analysed using generalised linear mixed models for binomial data with pen within stage and farm as a random effect. RESULTS: Tail and ear lesions showed the highest prevalence; however, large variation was observed between farms. In S1 the most prevalent welfare outcomes (presented as median prevalence) were poor body condition (4.4%), lethargic pigs (1.5%), scouring (20.3% of pens) and huddling (3.7%). In S2 and S3 outcomes related to injurious behaviour (tail lesions: 5.9% [S2] and 10.5% [S3], ear lesions: 9.1% [S2] and 3.3% [S3], and flank lesions: 0.4% [S2] and 1.3% [S3]), lameness (0.8% [S2] and 1.1% [S3]), bursitis (3.9% [S2] and 7.5% [S3]) and hernias (1.6% [S2] and 1.8% [S3]) were more prevalent. CONCLUSIONS: A large variation was observed for the recorded welfare outcomes corresponding to the different challenges pigs experience during the different stages of production on commercial pig farms. The prevalence of pigs affected by lesions caused by injurious behavior is a cause for concern and requires a collaborative approach to identify appropriate intervention strategies. This information could be used to further investigate appropriate benchmark values for different welfare outcomes that would assist the pig industry to develop appropriate health and welfare management plans to minimise welfare problems. At herd level such plans should include information on aspects of intervention, treatment, and the management of hospital pens as well as euthanasia.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 0,000 |
| 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) | 0,000 | 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 ».