The Canadian Cow-Calf Surveillance Network – productivity and health summary 2018 to 2022
Notice bibliographique
Résumé
Cow-calf surveillance data provide critical information about changing herd demographics, productivity, health, and management as well as the opportunity to investigate the impact of differing management practices. A national cow-calf network was established to collect baseline information on herd health, production performance measures, and management. Questionnaires were used to collect information on herd attributes as well as data for the calving season, breeding, pregnancy testing, and weaning for herds from across Canada. From 2018 to 2022, a total of 565 calving record questionnaires, representing 110,658 calving female records from 171 herds were returned, along with 543 herd breeding to weaning questionnaires. Suggested benchmark values based on the 25th percentiles from Western and Eastern Canada were determined to be <5% for non-pregnancy, <2% for calf death from birth to 24 h, and < 2% for calf death from 24 h to weaning. Herds from Eastern Canada were more likely to report any assistance at calving ( p < 0.001) than herds from Western Canada. Participating herds from the east had longer breeding ( p < 0.001) and calving ( p < 0.001) seasons than those from the west and were also more likely to use artificial insemination or embryo transfer ( p < 0.001). Timing of calving season and use of large pastures for calving were not associated with mortality at birth. Herds that started calving before April were more likely to have calves die before 30 d than those that started calving later; however, this difference was not observed between 30 d and weaning. Herds that started to calve earlier were also more likely to report treating more calves for bovine respiratory disease, diarrhea, and navel or joint infections as well as to calf deaths from respiratory disease. Calves from herds in the east were more likely to be treated or die from diarrhea than from the west. Females from herds that started calving later were less likely to be pregnant. The unique longitudinal productivity and health data resulting from this network established a national baseline to address region-specific needs for knowledge translation and solutions to enhance productivity and support sustainability.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».