Genotype by environment interactions for reproductive performance of North American purebred sows between North America and Southeast Asia
Bibliographic record
Abstract
Importing improved Western pig genetics into Southeast Asia has been a common practice to enhance the reproductive performance of pork production in the region. This study aimed to investigate the presence and magnitude of genotype-by-environment (GxE) interactions for sow reproductive performance of purebred North American genetics between temperate (North America) and tropical climates (Southeast Asia). Reproductive data from North American purebred Landrace (LR) and Large White (LW) sows, raised in Canada and in 2 Southeast Asia nucleus herds were used to estimate genetic parameters and quantify GxE. Data were recorded from 2015 to 2023 for 6 reproductive traits: total number born (TNB), number born alive (NBA), number stillborn (NSB), number mummified, age at first farrowing (AFF), and farrowing interval (FI). On average, TNB and NBA were lower in Southeast Asia than in Canada for both LR (by 13.0%) and LW (by 11.1%). The Canadian data showed higher estimates of heritability and repeatability than the Southeast Asia data for TNB, NBA, and NSB. Estimates of genetic correlations between parities for TNB, NBA, and NSB were not significantly different from 1 in Southeast Asia for both LR and LW, but they were significantly different from 1 for both breeds in Canada. Estimates of genetic correlations between Canada and Southeast Asia for TNB, NBA, and NSB were significantly different from 1 for the LW breed, ranging from 0.54 to 0.66, but were higher for the LR breed, ranging from 0.81 to 0.92, and not significantly different from 1. Estimates of genetic correlations between the 2 Southeast Asian herds; however, also revealed the potential presence of GxE within Southeast Asia, although these estimates were associated with high standard errors and were not significantly different from 1. Estimates of the genetic correlation between regions for FI and AFF were found to differ between breeds, with LR showing negative genetic correlations (-0.10 ± 0.33 and -0.59 ± 0.29 for FI and AFF, respectively), while LW showed positive genetic correlations for these 2 traits (0.73 ± 0.41 and 0.50 ± 0.11, respectively). The higher estimates of genetic correlations for reproductive traits between Canada and Southeast Asia for the LR breed indicate that LR sows may be more robust when exposed to a tropical climate, although there was no difference between the 2 breeds in the drop in average reproductive performance between Canada and Southeast Asia, nor was a seasonal effect on performance within Canada and Southeast Asia more pronounced for LW than LR. Further research is needed to investigate the differences in robustness and adaptability between these 2 breeds.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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".