The associations of early-life health and performance with subsequent dairy cow longevity, productivity, and profitability
Notice bibliographique
Résumé
Selecting and raising dairy animals that are more likely to reach their potential is a strategy to increase milk production efficiency and overall profitability. However, indicators are necessary for the early identification of animals that are less likely to perform well, allowing for their early culling and ensuring that resources are allocated to those with the highest potential. The objective of this study was to analyze the association between early-life animal health and performance with longevity, production, and profitability. After data cleaning, the following early-life measures (i.e., predictors) were available for 363 female calves born between June 2014 and November 2015 in eight dairy herds from New Brunswick, Canada (average: 45 calves/farm; standard deviation: 26.1 calves/farm; median: 42 calves/farm; range: 15 to 95 calves/farm): birth weight, weaning weight, weaning age, weaning average daily gain (weaning ADG), immunoglobulin G (IgG) serum concentration, the occurrence of navel infection, diarrhea, and pneumonia, and if animals received antibiotic treatment between birth and weaning. Their subsequent length of life (LL), length of productive life (LPL), lifetime cumulative energy-corrected milk (ECM), and lifetime cumulative milk value (i.e., response variables) were provided by the Canadian dairy herd improvement agency. Bayesian Additive Regression Tree models were trained for each response variable using 5-fold cross-validation. Models were evaluated using the RMSE and R2. The three most important predictors were identified using permutation, and the relationship between response variables and important predictors was assessed using accumulated local effect plots. The RMSE for LL, LPL, ECM, and milk value were 1.43 years, 1.37 years, 16 314.94 kg, and $CAD 11 525.68, respectively, whereas the R2 values were 0.30, 0.25, 0.29, and 0.29, respectively, indicating a moderate relationship between predictors and response variables. Non-linear relationships were found between the response variables and important predictors. Animals born with low or high birth weights were associated with decreased LL, LPL, ECM, and milk value. The highest LL, LPL, and milk value was observed for calves weaned between 1.9 and 2.0 months old, followed by a decline for calves weaned at older ages. The lowest LL and ECM were associated with weaning ADG of 0.786 kg/day, while 0.787 kg/day was associated with the lowest LPL. Lastly, both ECM and milk value were highest when serum IgG values were 1 659 mg/dL. These findings provide valuable insights for optimizing early culling decisions and enhancing the productivity and profitability of dairy farms.
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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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 ».