257 Impact of Mycoplasma hyopneumoniae infection on key performance metrics of swine production sustainability.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".