Estrous detection intensity and accuracy and optimal timing of insemination with automated activity monitors for dairy cows
Notice bibliographique
Résumé
The objectives of this observational study were to assess the ability of automated activity monitoring (AAM) to detect estrus for first insemination, the accuracy of detection, and the optimum interval from the estrus alert from the AAM system to insemination. Four commercial farms using 1 of 2 commercial AAM systems were studied over 1 yr. Cows were inseminated between 55 and 80 d in milk (DIM) based on AAM only, then by a combination of AAM and timed artificial insemination (AI). Blood progesterone was measured in 1,014 cows at wk 5, 7, and 9 postpartum; purulent vaginal discharge (PVD) was assessed at wk 5; and lameness and BCS at wk 7. Overall, AAM detected 83% of cows in estrus by 80 DIM. Cows that had 3 serum progesterone <1 ng/mL, had PVD, or were both lame and had BCS ≤2.5 has lesser odds of being detected in estrus by 80 DIM (62, 68, and 53%, respectively). Blood samples were collected on the day of 445 AI based on AAM and 323 timed AI. The proportion of cows not in estrus (progesterone >1 ng/mL) on the day of AI was similar between AAM (4 ± 1.8%) and timed AI (3 ± 1.2%). Managers elected, based on subjective criteria, not to inseminate 17% of cows for which an AAM estrus alert was issued, of which 43% were not in estrus. Activity data were extracted from AAM software for 1,399 AI. Onset of estrus was calculated using the same or similar data processing criteria as the AAM system. Producers recorded the time of AI. The interval from onset of estrus to AI was categorized as 0 to 8, 8 to 16, or 16 to 24 h. We found no effect of AAM system on the probability of pregnancy per AI, but noted an interaction of interval with parity. For multiparous cows, the probability of pregnancy per AI was 31%, which did not differ with the interval to AI. For primiparous cows, the odds of pregnancy were greater if AI occurred 0 to 8 h (49%) than 8 to 16 (36%) or 16 to 24 h (31%) after the estrus alert from the AAM. Automated activity monitoring can detect estrus for first AI in just over the length of 1 estrous cycle for over 80% of cows, but the remainder would likely require intervention for timely insemination. For multiparous cows, performing AI based on AAM once per day would not affect pregnancy per AI, but for primiparous cows AI within 8 h of the onset of estrus may be advantageous.
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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 | 0,001 | 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 | 0,001 | 0,001 |
| 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 ».