Magnitude of change in prepartum feed intake: Estimations using multiple classes of predictors and associations with transition metabolism, health, and milk production
Notice bibliographique
Résumé
The objectives of this study were to identify factors associated with the relative change in prepartum dry matter intake ( RCDMI ) of 273 cows fed individually, evaluate the performance of linear models to estimate RCDMI using different classes of predictors, and characterize the implications of RCDMI to transition metabolism, health, and subsequent milk production. Two periods of interest were established. Period 1 comprised d −21 to −12 relative to calving, when DMI was stable. Period 2 comprised d −4 to −1, when average DMI was distinctly declined. The RCDMI from period 1 to 2 was calculated as a percentage value, which ranged from −75 to 15% and averaged −18.1% (±15.0). Season, parity, body fatness, body weight, milk production in the previous lactation and at dry-off, and length of dry period were associated with RCDMI and explained 11% of the variation in all cows, and 19% when only parous cows were considered. Performance of linear models to predict RCDMI was improved when data on rumination and physical activities and target blood metabolites were added. The adjusted R 2 increased to values between 0.45 and 0.55, and selected models performed consistently in cross-validation analyses. To evaluate the implications of RCDMI, cows were ranked within parity according to RCDMI and classified into terciles as large decline ( LD ), moderate decline ( MD ), or small decline ( SD ). By design, DMI did not differ between tercile groups in period 1 (13.3 ± 0.2 kg/d), but differed substantially in period 2 (LD = 8.8; MD=11.2; SD=12.7 ± 0.2 kg/d), creating important differences in RCDMI among groups (LD = −33.8; MD=−16.2; SD=−3.4% ± 0.8%). At enrollment, cows in the LD and MD groups were heavier (LD = 788; MD=775; SD=750 ± 7 kg), and the proportion of cows with BCS >3.5 was higher in LD (LD = 63; MD=47; SD=38%). An interaction of group and time was observed for postpartum DMI, which started lower in LD than in SD cows, but equaled by the end of transition, and inverted at wk 13 and 14 after calving. Yields of energy-corrected milk were greater in LD than in SD cows, and both groups did not differ from MD (LD = 41.0; MD=40.3; SD=39.0 ± 0.5 kg/d). LD cows had decreased energy balance and greater concentrations of nonesterified fatty acids, β-hydroxybutyrate, and aspartate aminotransferase in serum, and greater glutathione peroxidase activity in plasma than SD cows. Larger declines in prepartum DMI were also associated with increased risk for postpartum disease, although the associations were only weak to moderate. In conclusion, a large decline in prepartum DMI was associated with important adjustments in the energy metabolism and antioxidants activities, and greater milk production in the subsequent lactation. These findings indicate that feed intake decline close to parturition is likely a normal response to physiological adaptations at the onset of lactation when cows are fed at libitum.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 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 ».