9 EVALUATION OF FERTILITY TRAITS OF HOLSTEIN CATTLE IN ARGENTINA
Bibliographic record
Abstract
Impaired fertility is the primary reason for culling in the United States (26.5% of all disposals) and fertility rates have steadily declined during the past 30 years. The objectives of this study were 1) estimate genetic parameters and evaluate genetic correlations for fertility traits based on data from milk recording programs, and 2) evaluate genetic fertility trends in Holstein cattle in Argentina. Data representing 3 282 843 lactations and 1 622 088 animals (cows and bulls from 1936 to 2007) were used for the analysis and obtained from official records maintained by the Argentinean Holstein Association (ACHA). Lactations were standardized to 305 DIM for milk, protein, and fat. Days open (DO), calving interval (CI), age to first calving (AFC), and daughter pregnancy rate (DPR) were selected for genetic parameter estimation. Daughter pregnancy rate was calculated as described by (Kuhn et al. 2004 J. Dairy Sci. 87, 2277–2284). Animal models by lactation for each fertility trait included contemporary group (dairy herd and calving year), calving month, animal effect, milk production as a covariate, and error term. Multiple-trait derivative-free restricted maximum likelihood (MTDFREML) was used to estimate covariance components. Solutions for fixed effects, breeding values, and sampling variances (accuracies) were obtained for each trait. The fertility index ($F = –0.28 × AFC ± 4.9 × CI) was calculated using the economic rates as reported by (Gonzalez-Recio et al. 2004 J. Dairy Sci. 87, 3053–3061). First lactation/parities were utilised for estimating correlations among BLUPs for DO, CI, DPR, AFC, and $F. In general, moderate and high genetic correlations were observed (from 0.238 to 0.999; P < 0.001). Days open and calving interval showed high negative associations with DPR (–0.999, –0.648) and $F (–0.612, Q0.981). Results from the correlation analysis suggest that CI and $F are qualified indicators of fertility in lactating dairy Holstein and relate well with all the other traits. The index, $F, benefits by including AFC as a measure of initial reproductive efficiency followed by the inclusion of CI which measures success of inseminations. Genetic trend for AFC showed a decrease of 2.76 days per year between 1970 and 2000 for sires. Similarly, trends for CI resulted in decreases of 0.45 days per year between 1970 and 2000 for sires. During the same period, DPR increased by 0.02 percent per year in sires. Using current dollars values, $F increased 2.99 dollars per year for sires. Results indicate progress in the genetic trend for fertility traits in the Holstein population of Argentina, with higher improvement in sires compared with dams. Trends visually showed faster improvement after 1980, possibly due to extensive importation of US and Canadian bulls and semen (72% of bulls born after 1986) and selection for productive life introduced in 1993. Supported by Asociacion Criadores de Holando Argentino (ACHA).
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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 | 0.002 | 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".