The effect of body weight during the rearing period on milk production in Québec dairy cattle
Notice bibliographique
Résumé
The Canadian dairy industry is composed of around 11,000 farms and approximately 1.4 million head, of which approximately 30 percent are heifers (Canadian Dairy Information Centre, 2018). Heifers are of great importance because they represent the future of dairy farms, and, without them, the herds could not evolve and continue producing over time. Producers select replacement heifers that have the potential to become more profitable than the existing cows that will eventually be replaced. Therefore, they should be raised to reach an adequate size and body weight for breeding, so that they can reproduce successfully, and subsequently become productive. This process of rearing replacement heifers can cost as much as 20 percent of the total production expenses on dairy farms (Delgado et al., 2015). The rearing period of a heifer does not only impact the actual growth rate of the animal early on; some researchers have also discussed longer-lasting effects on the animals' performance as lactating dairy cows (Soberon et al., 2012; Macdonald et al., 2005; Krpálková et al., 2014). The objective of this research was to determine the effects of body weight during rearing on the future milk production of Quebec dairy cattle. This was performed by looking at three periods of growth in a heifer's pre-lactation life – birth to weaning; pre-pubertal; and post-pubertal – and analysing the effect of their respective body weight categories on future milk production. Data were provided by the Quebec Dairy Herd Improvement Agency (Valacta), and included body-weight measurements, breeding records, and information for first, second, and third and plus lactations of Holstein dairy cattle. The study covered the years 2000 to 2015, and analyzed production and economic variables such as milk, protein, and fat yield (lactation and 305-day), gross profit, milk value and feed cost. The analyzed data consisted of a total of 22,312, 16,352 and 7,494 animals for the first, second and the third and plus lactations, respectively.While there was a tendency for heavier body weights up until 90 days of life (birth to weaning period) to have higher yields than lighter weights, the body-weight category of 110 to 124kg (not the heaviest) was found to have a significant effect on future first lactation milk, protein and fat production. Furthermore, pre-pubertal body weight had a significant effect on the first, second, and third and plus lactations where higher weights produced significantly higher first and second milk and milk-component yields. The effect of body weight during the post-pubertal period was significant on the first and second lactation where animals that weighed ≥410kg had higher milk, protein and fat yields.Some of the findings may have been influenced by the substantially lower number of observations in the third and later lactations, pointing to the industry's challenge of longer herd life. In addition, the lack of animals that had weight measurements (both a sufficient number, and a range throughout the complete rearing period) serves to encourage increased recording by producers and advisors, so that the data can be used for better lifetime analyses.
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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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».