Disbudding and dehorning practices for preweaned dairy calves by farmers in Wisconsin, USA
Notice bibliographique
Résumé
Many dairy farmers in North America disbud or dehorn their cattle to improve human and animal safety. The Farmers Assuring Responsible Management (FARM v. 4.0) program requires that disbudding be performed before 8 wk of age with pain-control medication. The objective of this observational cross-sectional study was to quantify disbudding and dehorning practices of Wisconsin dairy producers to target future extension programming. Responses from 217 Wisconsin dairy producers and calf raisers were collected via digital surveys distributed at extension events and through industry contacts. Of the 217 respondents, 188 performed on-farm disbudding themselves. Most respondents (61%) used caustic paste as their primary method, which was most commonly applied on the day the calf was born (53%). Hot iron was used by 32% of respondents, and surgical methods (gouge, scoop, or wire saw) were used by 6% of respondents. Hot-iron disbudding was most commonly performed at 4 to 8 wk of age (41%) and 1 to 4 wk of age (33%), whereas surgical methods were most commonly performed at 8 wk or older (73%). Pain-control medication was used by 43% of respondents. Specifically, 35% used an anti-inflammatory, and 21% used a local nerve block. Veterinary involvement in creating the disbudding protocol was associated with increased odds of using pain control. Respondents with a target weaning age of ≥10 wk had greater odds of complying with FARM disbudding requirements and were also more likely to use polled genetics. Respondents aged 18 to 34 and respondents with >60 calves were more likely to have made changes to their disbudding or dehorning protocol in the last decade. Although use of pain control was higher than in previous US studies, full adoption of pain management requires further extension efforts. Veterinarians appeared influential on adoption of pain control, and their involvement may encourage adoption of pain management. Further research should investigate how the implementation of new FARM v. 4.0 standards will change the disbudding and dehorning practices of American dairy producers.
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 | 0,001 |
| 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 | 0,001 |
| 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 ».