Effectiveness of a standardized footbath protocol for prevention of digital dermatitis
Notice bibliographique
Résumé
A footbath is the most common herd-level approach to control digital dermatitis (DD) in intensive dairy farming. However, wide variation in footbath design and protocols suggests a gap between evidence-based management practices and on-farm implementation. The objective was to evaluate effectiveness of a standardized footbath protocol in decreasing prevalence of active DD lesions in lactating dairy cattle. The protocol was based on current scientific literature, including footbath design and management. The M-stage classification system was used to score DD lesions. Scores were also combined into a simplified scoring system: no lesions (M0), active lesions (M1, M2, and M4.1), and chronic lesions (M3 and M4). A controlled intervention trial was conducted on 9 farms over 22 wk. Each farm served as its own control with data collected for 10 wk before and 12 wk after intervention. A total of 1,978 lactating cattle were assessed biweekly for DD lesions and leg cleanliness in the milking parlor. Lactating cattle were also inspected in the trimming chute at 3 time points: start, intervention, and end of trial. Intervention consisted of implementing an automated footbath that measured 3 m long, 0.50 m wide, held a fluid depth of 0.15 m, along with a weekly footbath protocol using 5% CuSO4 for 4 consecutive milkings, with footbath content replaced at a maximum of 200 cow passes. Multilevel logistic regression models for repeated measures were used to evaluate effects of the standardized footbath protocol in preventing active DD lesions. For the purpose of analysis, farms' within-herd prevalence of active DD lesions (at baseline) was assessed and categorized as low (<15%) or high (≥15%). Farms with low or high within-herd prevalence of active DD lesions at trial outset had a mean cow-level prevalence of active DD lesions of 8% (range, 2 to 13) and 31% (range, 18 to 43), respectively. At milking parlor inspections, apparent prevalence of active DD lesions decreased from the time of footbath intervention, but this effect interacted with the farms' baseline prevalence of active DD lesions. In that regard, on farms with high prevalence of active DD at baseline, apparent prevalence of active DD lesions decreased after intervention, whereas on farms with low prevalence of active DD at baseline, apparent prevalence of active DD lesions did not change. At the cow level, poor leg cleanliness was associated with higher prevalence of active DD lesions. At trimming chute inspections, prevalence of active DD lesions decreased from start to the end of the trial (22 and 14%, respectively); concurrently, prevalence of feet with no DD lesions (M0) increased (39 and 48%). We concluded that on farms with high DD prevalence, implementation of proper footbath design and improvement of footbathing management will decrease prevalence of active DD lesions and increase prevalence of feet without DD lesions. In addition, improving cow cleanliness will further result in control of active DD lesions.
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 | 0,001 |
| 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 ».