PSIII-13 Genetic parameters and the purebred–crossbred genetic correlation for growth, carcass, and meat quality traits in pigs
Bibliographic record
Abstract
Abstract Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in commercial crossbred pigs and purebred-crossbred genetic correlations are necessary for a successful breeding program. The objectives of this study were to 1) estimate genetic parameters for growth, meat quality and carcass traits in a purebred sire line and related commercial crossbred pigs and 2) estimate the corresponding genetic correlations between purebreds and crossbreds (rpc). We analyzed 115266, 10927 and 43057 purebred records for growth, meat quality (n = 4) and carcass traits (n = 7), respectively. For crossbreds, there were 2000 pigs with growth records, with 900 of them having meat quality and carcass data. A series of univariate and bivariate analyses were used to estimate genetic parameters and rpc. Growth showed moderate heritability (0.20 ± 0.10 to 0.25 ± 0.01) in both purebreds and crossbreds. Heritability estimates for meat quality traits ranged from 0.21 ± 0.03 to 0.42 ± 0.04 in purebreds and from 0.17 ± 0.14 to 0.47 ± 0.15 in crossbreds. Carcass traits had higher heritability estimates in purebreds compared to crossbreds, except for hot carcass weight (0.10 ± 0.02 vs. 0.24 ± 0.16). Genetic correlations among meat quality traits were variable in both populations, whereas genetic correlations among carcass traits were similar in purebreds and crossbreds. Estimates of rpc were high for growth (0.99 ± 0.5) and for meat quality traits (0.94 ± 0.39 to 0.99 ± 0.2), except for Minolta color (-0.48 ± 0.56). Carcass traits had moderate to high estimates of rpc (0.64 ± 0.4 to 0.92 ± 0.3). Carcass fat had a negative estimate of rpc (-0.1 ± 0.5). However, ultrasound fat as an indicator trait for carcass fat had a high positive estimate of rpc (0.88 ± 0.14). Our results indicate that selection in purebreds can be efficient to improve these traits in both purebreds and crossbreds but for some traits, genetic gain can be improved by applying combined crossbred and purebred selection. Funding provided by Genome Canada and the National Research Council.
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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 | 0.002 |
| 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 | 0.000 | 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".