Productive traits of daughters of sires of Holstein breed depending on the country of origin and genotype according to gene CSN3
Bibliographic record
Abstract
Numerous studies have proven the effect of the allele B of the kappa casein gene (CSN3) on protein milk content, because the protein controlled by this allele has a number of distinctive features: difference in micelle size, higher protein content, greater stability when heated and frozen, better properties for cheese making (shorter coagulation time, coagulate of a denser consistency and a higher cheese yield by 5–10 %). The purpose of the research was to study the frequency of occurrence of alleles and genotypes of the kappa casein gene (CSN3) in sires of Holstein breed, depending on the country of origin, and to trace the infl uence of the identifi ed genotypes on the productive traits of the daughters of sires (milk yield, fat and protein content in milk). It was revealed that the highest frequency of occurrence of the desired allele B kappa-casein was found in sires of Dutch and Canadian breeding 33,3 and 34,7 %, respectively. The highest frequency of occurrence of homozygous genotype CSN3 BB was found in Dutch–bred sires – 22,2 %. The frequency of occurrence of the heterozygous CSN3 AB genotype was higher than others in Canadian–bred sires – 36,1 %. The best milk yield was characterized by the daughters of Canadian and Dutch-bred sires with CSN3 AA genotype, among the daughters of Germanbred sires it was CSN3 AB. The highest amount of fat in milk of daughters of sires of Dutch origin was found in cows with the sire’s genotype AB, in daughters of sires of German and Canadian breeding itwas AA, but the indicators practically did not differ from those of daughters of sires with the genotype AB. The highest protein content in milk was found in the daughters of sires of diff erent origins with the allele B of the kappa-casein gene.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".