Genetic parameters and correlations for female reproductive performance and early growth performance of piglets in Landrace breed across various regions of Vietnam
Bibliographic record
Abstract
This study aimed to estimate the genetic parameters for reproductive and early performance traits in Vietnam-purebred Landrace pigs. Traits analysed included the total number of pigs born (TB), number of pigs born alive (NBA), number of weaned pigs (NW), individual birth weight (BW), litter birth weight (LBW), individual weaning weight (WW), and litter weaning weight (LWW). This analysis was based on 5294 farrowing records collected from 2013 to 2019 from 1500 Landrace sows across three locations in Vietnam. Genetic parameters were estimated using ASReml-R. Heritability estimates for reproduction traits were negligible, below 0.10, ranging from 0.019 ± 0.012 to 0.071 ± 0.014, with repeatability ranging from 0.019 ± 0.014 to 0.152 ± 0.016. The genetic correlations ranged from −0.788 ± 0.09 to 0.993 ± 0.163, with the highest between IBW and LWW and the lowest between TB and IBW. NBA showed positive and moderate to high correlations with other traits, except for a negative correlation with IBW. Phenotypic correlations among reproductive traits ranged from −0.42 ± 0.013 to 0.879 ± 0.004. Negative phenotypic correlations were observed between TB, NBA, and NW with IBW and IWW, while positive correlations were observed with LBW and LWW. In conclusion, the heritability for reproductive performance and early growth traits in Vietnam-purebred Landrace pigs is negligible, indicating limited genetic progress from direct selection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".