Significance of breeding value indicators for prediction of milk yield
Bibliographic record
Abstract
A comparative assessment of the significance of various indicators of the breeding value of breeding bulls for predicting milk yield in the highly productive herd of the farm economy "Alfa" was carried out. The milk yield of cows, whose bulls-fathers were evaluated in Ukraine and abroad, was studied. It was established that in the period from 2009 to 2014, the milk yield of first-calf heifers increased by 23.9 % and reached 5894.3 kg. Accordingly, during the specified period, most of the quantitative indicators of the breeding value and milk productivity of the bulls' daughters also increased: the breeding value of the parent bulls in terms of milk yield increased from +245.3 kg in 2009 to +540.4 kg in 2014; the breeding value of parent bulls in terms of the total amount of milk fat per lactation increased from +10.2 kg to +29.7 kg. A correlation analysis of the relationships between various indicators of breeding value of parent bulls and the milk yield of their daughters was carried out. It was established that the actual milk yield of first-calf heifers in FE "Alfa" most (correlation coefficients r higher than 0.8) and most significantly (p<0.001) depended on the average milk yield and amount of milk fat yield of bull's daughters in the herds where the breeding value of these bulls was evaluated. The breeding value of the sire bulls by the amount of milk fat yield was also characterized by high (r=0.675) and significant (p<0.01) relationship with the actual milk yield of the first-calf heifers (daughters of these sires). The variance analysis of the influence of the breeding value estimation method of breeder bulls (BV, ETA, ZW, DRV, RPC) on the actual milk yield of their daughters during the first lactation established that this influence was significant (p=0.001), and the power of influence was η2=0,59. Significant differences were mostly observed between milk yields of first-calf heifers whose parent bulls were evaluated abroad and in Ukraine. The biggest difference in terms of actual milk yield was revealed between the daughters of bulls evaluated by the ETA method (Canada) and by the "daughter-of-the-same-age (DRV)" method (Ukraine). This difference was 2640 kg of milk (p<0.01) in favor of firstcalf heifers from Canadian bulls. Key words: breeding bulls, breeding value, milk productivity, daughters of bulls, milk yield, selection index, evaluation method.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 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".