257 Impact of Mycoplasma hyopneumoniae infection on key performance metrics of swine production sustainability.
Notice bibliographique
Résumé
Abstract Mycoplasma hyopneumoniae (M. hyopneumoniae) is the primary causative agent of enzootic pneumonia, a highly prevalent respiratory disease affecting pigs in the late grow-finish period.1 Infection with this bacterium is associated with reduced animal welfare, performance, and decreased production efficiency. Mycoplasma hyopneumoniae is a contributor to the Porcine Respiratory Disease Complex, along with other agents like porcine reproductive and respiratory syndrome virus (PRRSV).1 Infectious diseases decrease production efficiency and can compromise the sustainability of pork production.2 Using literature on pig performance from M. hyopneumoniae experimental infections and lifecycle impact estimates, the environmental impact of M. hyopneumoniae infection was calculated, which increased as days on feed did.3 However, it is unknown if similar performance is observed in commercial conditions. Therefore, the objective of this study was to assess production performance metrics in M. hyopneumoniae infected pigs under commercial conditions to inform estimates of sustainability in pork production. This study utilized data from three conveniently selected pig flows (A, B, and C) in a US production system. Eight years of historical data were evaluated for each flow. During six of the years in the study, Flow A was positive for M. hyopneumoniae at the sow farm. Flows B and C were negative for M. hyopneumoniae infection and served as controls. All flows were sourced from PRRSV positive sow farms. A retrospective comparison using exploratory data and time series analyses was conducted to identify differences in flows based on M. hyopneumoniae infection and co-infection with PRRSV. Variables related to feed utilization, medication, mortality, carcass weight, and sales were assessed to identify trends. The time series analysis showed the peak mortality was 2.3 times higher in flow A compared to flows B and C. The lowest ADG in flow A was 1.5 times lower than that in the control flows. The peak disruption in multiple performance metrics for flow A, was observed approximately nine months after a Mycoplasma hyopneumoniae outbreak. Metrics displaying peak disruption on average included: mortality, total medication cost, average daily feed intake, gain to feed, substandard sales, average carcass weight, average daily gain, and days first market (Table 1). In this dataset, infection with M. hyopneumoniae resulted in increased medication cost, decreased growth rate and carcass weight, leading to reduced production efficiency, which can ultimately compromise pork production sustainability. A synergistic effect of co-infection of M. hyopneumoniae and PRRSV was observed. The timing of peak disruption in production performance parameters was evidenced several months post the initial M. hyopneumoniae outbreak. Results from this study suggest that the impact of swine diseases on sustainability of pork production requires analysis of commercial farm data as production dynamics are not usually captured in the scientific literature. 1Pieters M., Maes D. (2019). In: Diseases of Swine. 11th Ed. Blackwell Pub. J. Wiley & Sons, Inc. 2Capper, J. (2023). One Health Outlook, 5(1). 3Krebs, S. et al. (2024). Proc. of ASAS, Calgary, Canada.
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 | 0,002 |
| 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 | 0,000 | 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) | 0,001 | 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 ».