Effect of dry-off management on milking behavior, milk yield, and somatic cell count of dairy cows milked in automated milking systems
Notice bibliographique
Résumé
Milk production may be reduced before dry-off to decrease the risk of cows developing intramammary infections during the dry period. Such reductions in milk may be possible in automated milking systems (AMS) where milking frequency and feed allocation at the AMS can be controlled at the cow level. This study investigated the effect of dry-off management of cows milked in AMS on milk yield, milking behavior, and somatic cell count (SCC). Using a 2 × 2 factorial arrangement of treatments, applied from d 14 to 1 before dry-off, 445 cows from 5 commercial dairy farms in Quebec, Canada, were assigned within farm to either (1) reduced feed [RF; allowed a maximum of 0.75 kg/d of AMS pellet for the first week (14 to 8 d before dry-off) of treatment, and 0.50 kg/d for the second week (7 to 1 d before dry-off) of treatment], or (2) nonreduced feed (NF; allowed up to 2 kg/d of AMS pellet), and either (1) reduced milking (RM; reduced to 2 milkings/d or as many times as required to yield 17 kg/milking), or (2) nonreduced milking (NM; allowed up to 6 AMS milkings/d) and no maximum production. Feed and milking behavior data, as well as milk yield and SCC were collected from the AMS software. The RF cows had lower AMS feed delivered during the treatment period, as per the experimental design. Across the treatment period, the NF-NM cows had the highest milking frequency (2.7 times/d), followed by the RF-NM cows (2.4 times/d), and then both of the RM groups (1.8 times/d), which did not differ from each other. All cows, except the NF-NM cows, were gradually milked less frequently as dry-off approached. Across the entire 2-wk treatment period before dry-off, cows with RM allowance experienced a higher reduction in milk yield compared with the cows with no milking allowance restrictions (-4.8 vs. -3.6 kg). Similarly, cows with a RF allocation tended to have a higher reduction in milk yield than cows with NF (-4.6 vs. -3.7 kg). As result, those cows with both reduced milking permissions and feed allocation at the AMS experienced the greatest drop in milk production before dry-off. There were no differences between treatments for milking frequency or yield in the next lactation. Somatic cell score (calculated from SCC) was not different between treatments in the 2-wk or day before dry-off, nor in the first month after calving. Overall, these data suggest that reducing both milking frequency and feed quantity in the AMS is the most efficient method to decrease milk yield before dry-off, without negatively influencing milking frequency or yield in the next lactation, as well as without affecting milk quality.
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 | 0,000 |
| 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 | 0,000 |
| 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 ».