Characteristics of estrous behaviour in heifers and lactating cows and its associations with fertility
Notice bibliographique
Résumé
Detection of estrus in dairy cows is challenging, partly because of poor behavioural expression. Automated activity monitors allow quantification of estrus expression based on restlessness. The main goals of this thesis were to use automated measurements and visual observation of behaviour to increase understanding of estrus characteristics, variation among animals, risk factors for poor expression, and its association with fertility. In the first study, the behaviour of heifers was video-recorded and activity peaks were identified from accelerometer data; estrus was validated by ovarian ultrasonography. Chin rest, sniff, back mount, crossover, and follow had the largest increase in frequency during estrus. Estrus relative increase in walking activity (290 ± 160%) and duration (14 ± 4 h) varied greatly and were affected by estrus order, season and time of the day. The second study investigated how estrus affected automated measurements of lying and standing behaviour, a less explored aspect of estrus. At estrus, bout frequency was lower, daily standing time was greater, and heifers stood uninterruptedly for twice longer than at baseline. Relative changes in standing behaviour at estrus were smaller for estrus starting between 1200 h and 0300 h. The third experiment investigated the agreement between estrus characteristics in heifers fitted with two accelerometers. Both systems were precise (PPV = 84.7% [Heatime] and 98.7% [IceTag]) and provided similar characterization and timing. Plasma estradiol was not correlated with follicle diameter, duration, intensity, or presence of estrus signs. Finally, estrus lying behaviour of lactating cows and its associations with fertility were studied. Daily lying time and bout frequency were reduced at estrus (65 ± 21% and 65 ± 24% of baseline). Ovulation and pregnancy at d 32 after AI were 4.9 and 1.6 times more likely if estrus lying time was < 75% of baseline. Collectively, results suggest potential application of lying behaviour towards fertility prediction. We have also highlighted features such as variability, risk factors and basal activity that can contribute to assessment of methods and practices for increased expression. Additional future directions include investigation of physiological bases of estrus-fertility association and real-time applications of characterization data.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».