Monitoring inbreeding trends and inbreeding depression for economically important traits of Holstein cattle in Iran
Bibliographic record
Abstract
Pedigree information of 852,443 registered Holstein cows and bulls, collected by the Animal Breeding Center of Iran from 1971 to 2007, was used to calculate inbreeding coefficients and their effect on production, reproduction, somatic cell count, calving ease, and longevity traits. The average inbreeding coefficient for the entire population was 2.90%, ranging from zero to 47.03%. The rates of inbreeding from 1989 to 2007 were 0.22 and 0.15% per year for females and males, respectively. The rates were higher after 2000, being 0.31 and 0.21% per year for females and males, respectively. Inbreeding had a deleterious effect on most traits. For the first 3 lactations, the inbreeding depression per 1% increase in inbreeding was -18.72, -16.19, and -27.38 kg for milk yield, -0.443, -0.367, and -0.690 kg for fat yield, and -0.476, -0.425, and -0.66 kg for protein yield, respectively. For all reproductive traits, the observed undesirable effect of inbreeding was not significant, except for the calving interval (0.53 d per 1% increase in inbreeding) in the third parity and age at first calving (0.45 d per 1% increase in inbreeding). Calving ease in heifers and cows was significantly influenced by the inbreeding of the dam, indicating that highly inbred cows had a higher incidence of difficult calvings. The estimate of inbreeding depression for somatic cell score was low and significant only for the third lactation. However, animals with high inbreeding coefficient tended to have higher somatic cell scores than animals with low inbreeding coefficients. For type traits, the influence of inbreeding was significant only for stature, chest width, body depth, size, rear udder height, suspensory ligament, udder depth, and front and rear teat placement. Cows with high levels of inbreeding coefficient were at higher relative risk of being culled.
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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 | 0.000 |
| 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".