Identification of polymorphisms influencing feed intake and efficiency in beef cattle
Bibliographic record
Abstract
Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI (P < 0.05). The largest single SNP allele substitution effect for RFI was -0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI (r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle.
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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) | 0.001 | 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".