Selection for lean growth rate and correlated responses in litter traits in a synthetic line of Yorkshire-Meishan pigs
Bibliographic record
Abstract
Selection for lean growth rate (LGR) was conducted for four generations in a synthetic line of Yorkshire-Meishan pigs to study the effectiveness of selection for LGR and correlated responses in litter traits. Lean growth rate was estimated from ultrasound measurements of 10th-rib backfat thickness and longissimus muscle area. In the selection line, 7 boars and 20 gilts with the highest LGR were selected to produce the next generation. The generation interval was 13 mo and the average selection differential per generation was 1.1 phenotypic standard deviation units. A contemporaneous control line was maintained by randomly selecting 5 boars and 15 gilts. Data from a total of 1057 pigs sired by 58 boars and out of 133 sows were available from the two lines. Selection responses were estimated from deviations of the selection line from the control line using least squares (LS) and by multiple trait derivative-free restricted maximum likelihood analysis using an animal model (AM). The estimate of response to selection per generation using LS was 9.4 ± 0.95 g d –1 for LGR. The corresponding estimate from the AM was 9.8 ± 0.51 g d –1 . Correlated responses in litter traits were regressed on generation. For the LS method, regression coefficients were negative but not significant (P > 0.05) for total number born, number born alive, and number at 21 d and at 42 d. Significant, positive correlated responses occurred in 42-d litter weight and 21-d piglet weight (P < 0.05). For the AM method, the regression coefficients were also negative, but were not significant (P > 0.05) for numberalive at birth, at 21 d, and at 42 d. A significant positive correlated response occurred only for 42-d litter weight (P < 0.05). Although results are based on a population of limited size, it can be concluded that selection for LGR in a synthetic line is effective and should have little effect on litter traits. Key words: Pigs, selection, lean growth rate, correlated response
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".