Comparing production metrics and financial efficiency in production-limited dairy herds
Notice bibliographique
Résumé
This retrospective observational study examined the relationships between production metrics and financial efficiency on dairy farms operating within a production-limited system in Canada. In such a system, production quotas serve as the primary constraint on herd expansion. Canadian financial advisors, including accountants and lenders, predominantly use earnings before interest, taxes, depreciation, and amortization (EBITDA) as their key success metric at the herd level. For comparative purposes, they often use quota holdings measured in kilograms of butterfat rather than cow numbers as the denominator. Data were collected from 42 Canadian farms for the years 2017 through 2021. Financial statements were standardized and adjusted to account for unpaid labor and dividends. Multivariable linear regression was used to describe the relationship between 17 commonly used metrics-including those related to milk production, reproduction, transition, replacements, and turnover-and the annual EBITDA per kilogram of butterfat quota (EBITDA/kg). Milk production per cow (ECM; 39 ± 4 kg/d) was not significantly associated with EBITDA/kg (Can$1,851 ± Can$1,000; Can$1 = US$0.72). Four metrics exhibited significant associations with EBITDA/kg. Specifically, labor as a percentage of revenue, purchased feed/kg of butterfat quota, and DIM demonstrated negative associations, whereas the percentage of the herd dry between 45 and 75 d exhibited a positive association. Earnings before interest, taxes, depreciation, and amortization serves as an indicator of the efficiency with which raw materials are converted into profit. The findings suggest that higher production levels are unrelated to increased milk production efficiency within a production-limited system at the herd level. Certain management factors, such as purchased feed/kg and labor, may result in suboptimal resource use. Conversely, factors such as DIM and days dry may influence the cow's efficiency in converting feed into milk at both the cow and herd level. Although the lack of association between production and EBITDA may not apply to non-production-limited markets, expanding the focus beyond production metrics to include financial efficiency enables advisors in all markets to identify management practices that may impede optimal milk production. This research highlights the importance of collaboration between production and financial advisors. Comparing key efficiency indicators alongside EBITDA/kg will ensure that producers concentrate on areas with the greatest potential for financial improvement.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 tête enseignante, 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 ».