COMPARATIVE ANALYSIS OF THE EVALUATION RESULTS OF HOLSTEIN BLACK-MOTLEY BREEDING BULLS BY THEIR DAUGHTERS’ PRODUCTIVITY BASED ON OFFICIAL INSTRUCTIONS AND BLUP MODEL
Bibliographic record
Abstract
According to the current “Instruction” used in dairy cattle selection and breeding in the Republic of Kazakhstan, bulls-producers of dairy breeds are assessed according to the their offspring quality based on the principle of “peer daughter”. This means that the phenotypic indicators of the daughters of the tested bulls are compared with the corresponding indicators of their peers. In European countries with developed dairy cattle breeding, as well as in Canada, the USA, etc., to ensure a reliable forecast of the genetic value of individuals (primarily, bulls-producers), use is made of the best linear unbiased forecast method (BLUP method). This method implies that the breeding value of producers is determined by the deviation values of the development of traits of the examined animal from its average values in the population. Especially urgent area is the research aimed at improving breeding programs, including assessing the breeding value of bulls-producers of dairy breeds using BLUP methods based on the productive qualities of the mass of dairy cattle in the Republic of Kazakhstan. The research material included the data on the phenotypic indicators of the milk productivity of first-calf cows (the amount of milk yield, the content of fat and protein in milk, the yield of milk fat and protein) of the Holstein black-motley dairy cattle breed, obtained from the information and analytical database of the Republic of Kazakhstan for 2016–2017. It was found that when evaluating according to the official “Instruction”, 16 sires out of 256 bulls (6.2%) got the stud category in 2016, 14 sires (9.2%) out of 152 bulls in 2017, and – 30 sires of 249 bulls (12.0%) over the cumulative period. The results of the conducted research prove that the use of the classic “Instructions” in dairy cattle breeding has lower efficiency (by 42.8–90.0%) as compared with the assessment of the breeding value of bulls based on the BLUP method.The selection of sire bulls into breeding groups based on the “peer daughter” methodology is not reliable enough and rather ineffective. Comparing the results of assessing the breeding qualities of sire bulls, obtianed using two methods in all compared periods (2016, 2017, 2016–2017), the authors established a clear superiority of the BLUP method over the current Instruction used in the Republic of Kazakhstan.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".