Precalving nutritional factors associated with colostrum quality and yield in Québec dairy herds
Notice bibliographique
Résumé
The objective of this prospective longitudinal study was to identify precalving dietary ingredients, nutrient composition, cow characteristics, and herd management affecting colostral Ig G concentration, Brix values, and yield of multiparous Holstein cows in Québec commercial Holstein dairy farms.Data from 364 multiparous cows from 51 herds were analyzed in this study.In each herd, 3 to 12 cows (average of 6.5 cows per herd) ranging from 0 to 33 d precalving (median of 13 d precalving) were enrolled and sampled.One visit was conducted before calving in each herd at which cows were blood sampled, BW was estimated by heart girth circumference, and all dietary ingredients and TMR given to the cows were sampled, and their respective quantities offered were recorded.Producers were asked to take a sample of colostrum at the first milking after calving and to complete a form regarding the calving and colostrum management of each cow.Colostrum samples were analyzed for their IgG concentration and Brix % value.Rations were reconstituted before nutrient composition analysis by wet chemistry.To reduce the number of interdependent variables to include in the multivariable models, a principal component analysis was carried out on data relative to the ration.Univariable models were performed with colostrum yield and colostral IgG and Brix values as dependent variables.Independent variables leading to P < 0.20 at the univariable level were retained in the multivariable linear regression model followed by a backward elimination.Colostral IgG, Brix, and yield averaged 56.1 (SD = 23.7)mg/mL, 23.9% (4.6%), and 5.9 (3.9) kg, respectively.Colostral IgG and Brix led to the same final models.Second-parity cows had lower colostral IgG concentrations than third and higher parity cows.Colostral IgG was negatively related to mineral and protein supplements and positively to commercial energy supplements.A negative relationship was observed between colostral IgG and time between calving and colostrum collection.Plasma nonesterified fatty acid concentration and time between calving and the first milking were positively related to colostrum yield.A dry period length of 65 d and more tended to lead to a greater colostrum yield than a dry period length of 51 d or less.Decreasing prepartum dietary fiber, ash, Ca, Mg, and Fe and increasing energy were related to greater colostrum yield.The model including diet, cow, and herd management factors explained respectively 34%, 40%, and 51% of the IgG concentration, Brix %, and colostrum yield variability (pseudo-R 2 ).In summary, the studied factors explained a moderate part of the colostrum yield and IgG variability.
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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 | 0,001 | 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 | 0,001 | 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) | 0,001 | 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 ».