PSIV-24 Genetic analysis of the service sire effect on survival of swine from birth to market weight.
Bibliographic record
Abstract
Abstract Mortality from birth to market weight in swine imposes substantial economic losses on pork production systems and raises critical animal welfare concerns. While genetic selection has predominantly targeted maternal and direct genetic effects, the role of service sires in shaping offspring survival remains poorly characterized, limiting opportunities for optimizing breeding strategies. Quantifying the genetic contribution of service sires to offspring survival may provide an opportunity to improve selection for survival traits. Thus, this study aimed to estimate the heritability of service sires on seven survival-related traits from birth to market weight. The studied traits included total number of piglets born (TNB), total number of piglets born alive (NBA), survival rate at birth (SRB), total number weaned (TNW), survival rate from birth to weaning (SRW), total number of individuals reaching market weight (TNM), and survival rate from weaning to market weight (SRM), The dataset included records from 9,828 litters of the Canadian Landrace breed. The phenotypic records of litter originated from a total of 4,067 dams and 788 service sires. The significance of fixed effects (herd-year-season and number of services), covariates (inbreeding of litter and dam, parity, farrowing age of dam within parity, lactation length of previous parity, previous weaning to conception interval), and random effects (additive genetic effects of dam and sire, permanent environmental effect of dam, and common litter effect of dam) were determined using univariate models in ASReml 4.2. Only the significant effects were retained in the final model for variance component estimation for each trait. The estimated heritabilities (±SE) for the service sire were low at 0.066±0.009 for TNB, 0.059±0.008 for NBA, 0.018±0.005 for SRB, 0.049±0.008 for TNW, 0.014±0.004 for SRW, 0.032±0.006 for TNM, and 0.026±0.006 for SRM. On average, the difference in the estimated EBVs between the top and bottom 10% of service sires corresponded to an increase of 3.77 TNB, 3.44 NBA, 0.03 SRB, 2.58 TNW, 0.04 SRW, 1.96 TNM, and 0.10 in SRM per litter. These results indicate that sire selection could be used to improve piglet survival, although direct genetic gains may be limited due to the low heritability of the traits. However, the low heritabilities highlight the potential for genomic selection, which leverages genome-wide markers to capture additive genetic variance beyond what is detected by pedigree-based methods and offers a viable strategy to improve pre- and post-weaning survival. Further research should explore integrating genomic information to refine selection strategies for service sires on these critical yet low-heritability survival traits.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".