Short-term selection for yearling weight in a small-experimental Iranian Afshari sheep flock
Bibliographic record
Abstract
A selection experiment was initiated in 2000 in an Afshari sheep flock at the department of animal breeding and genetics of the University of Zanjan, Iran. The aim was to evaluate the response of Afshari sheep to selection for yearling live weight. Here, we evaluate the results of this breeding program obtained between 2000 and 2005. Traits studied were birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (WWDG) and average daily gain from weaning to yearling age (YWDG). Mixed model methodology based on a multi-trait animal model was employed to estimate (co)variance components and corresponding genetic parameters. Estimates of breeding values were obtained by the best linear unbiased prediction (BLUP) method. Generation intervals on the four genetic pathways were estimated as the average age of parents at the birth of their progeny kept for reproduction. The heritability estimates were 0.34, 0.27, 0.14, 0.20 and 0.01 for BW, WW, YW, WWDG and YWDG, respectively. Estimates of genetic correlations among traits studied were positive, and ranged from low (0.07, YW/WWDG) to high (0.76, YW/YWDG). Genetic improvements over the experiment based on estimated breeding values were 0.104, 0.824, 1.247, 0.005 and ≈0.00 kg for BW, WW, YW, WWDG and YWDG, respectively. Annual genetic gain for YW was relatively high, 0.311 kg yr-1, which demonstrated the effectiveness of the implemented breeding program. Correlated responses in BW, WW, WWDG and YWDG were 0.021, 0.167, 0.001 and ≈0.00 kg yr-1, respectively. Estimates of heritabilities and observed genetic trends indicated that selective breeding can lead to significant genetic improvement in Afshari sheep. The average generation interval was estimated to be 3.35 yr. The shorter generation interval was observed on the sire side compared with the dam side (3.30 yr vs. 3.78 yr), indicating faster generation turnover for sires than for dams. Key words: Sheep, animal model, genetic trend, generation interval, heritability
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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 | 0.000 | 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 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".