Genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit of feedlot cattle1
Bibliographic record
Abstract
Leptin is the hormone product of the obese gene that is synthesized and predominantly expressed by adipocytes. This study estimated the genetic variation in serum leptin concentration and evaluated the genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit. There were 464 steers with records for serum leptin concentration, performance, and efficiency of gain and 381 steers with records for carcass traits. The analyses included a total of 813 steers, including those without phenotypic records. Phenotypic and genetic parameter estimates were obtained using SAS and ASREML, respectively. Serum leptin concentration was moderately heritable (h2 = 0.34 +/- 0.13) and averaged 13.91 (SD = 5.74) ng/mL. Sire breed differences in serum leptin concentration correlated well with breed differences in body composition. Specifically, the serum leptin concentration was 20% greater in Angus-sired steers compared with Charolais-sired steers (P < 0.001). Consequently, ultrasound backfat (27%), carcass 12th-rib fat (31%), ultrasound marbling (14%), and carcass marbling (15%) were less in Charolais- than Angus-sired steers (P < 0.001). Conversely, carcass LM area (P = 0.05) and carcass lean meat yield (P < 0.001) were greater in Charolais- compared with Angus-sired steers. Steers with greater serum leptin concentration also had greater DMI (P < 0.001), greater residual feed intake (P = 0.04), and partial efficiency of growth (P = 0.01), but did not differ in feed conversion ratio (P > 0.10). Serum leptin concentration was correlated phenotypically with ultrasound backfat (r = 0.41; P < 0.001), carcass 12th-rib fat (r = 0.42; P < 0.001), ultrasound marbling (r = 0.25; P < 0.01), carcass marbling (r = 0.28; P < 0.01), ultrasound LM area (r = -0.19; P < 0.01), carcass LM area (r = -0.17; P < 0.05), lean meat yield (r = -0.38; P < 0.001), and yield grade (r = 0.32; P < 0.001). The corresponding genetic correlations were generally greater than the phenotypic correlations and included ultrasound backfat (r = 0.76 +/- 0.19), carcass 12th-rib fat (r = 0.54 +/- 0.23), ultrasound marbling (r = 0.27 +/- 0.22), carcass marbling (r = 0.76 +/- 0.21), ultrasound LM area (r = -0.71 +/- 0.19), carcass LM area (r = -0.75 +/- 0.20), lean meat yield (r = -0.59 +/- 0.22), and yield grade (r = 0.39 +/- 0.26). Serum leptin concentration can be a valuable tool that can be incorporated into appropriate selection programs to favorably improve the carcass merit of cattle.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".