Phenotypic and genetic parameters of circadian rhythms from core body temperature profiles and their relationships with beef steers’ production efficiency profiles during successive winter feeding periods
Bibliographic record
Abstract
This 2-year study evaluated differences in circadian parameters obtained from measures of core body temperatures using telemetric reticulo-rumen and rectal devices during two winter feeding regimes in western Canada. The study also estimated phenotypic correlations and genetic parameters associated with circadian parameters and other production traits in each feeding regime. Each year, 80 weaned steer calves (initial age: 209 ± 11 days; BW: 264 ± 20 kg) from the same cohort were tested over two successive regimes, Fall-Winter (FW) and Winter-Spring (WS) at Lanigan, Saskatchewan, Canada. The steers received forage-based rations in both regimes where the individual feed intake was measured with automatic feeding units. During the trial, the reticulo-rumen (RTMP) and rectal (RCT) temperatures were simultaneously measured every 5 min using telemetric devices. These were used to calculate the circadian parameters (Midline Estimating Statistic Of Rhythms, amplitude, and acrophase/peak time) for both temperature measures. Growth and efficiency performance traits were also determined for all steers. Each steer was assigned into inefficient, neutral, and efficient classes based on the SD of the residual feed intake (RFI), residual gain (RG), and residual intake and gain (RIG) within each year and feeding regime. Higher ( p < 0.0003) RTMP and rectal temperature MESORs were observed in the Fall-Winter compared to the Winter-Spring regime. While the two test regimes were different ( p < 0.05) for the majority of the RTMP or RCT temperature parameters, they did not differ ( p > 0.10) with the production efficiency profiles. The heritability estimates were higher in FW (0.78 ± 0.18 vs. 0.56 ± 0.26) than WS (0.50 ± 0.18 vs. 0.47 ± 0.22) for the rumen and rectal MESORs, respectively. There were positive genetic correlations between the two regimes for the RTMP (0.69 ± 0.21) and RCT (0.32 ± 0.59). There was a negative correlation ( p < 0.001) between body temperature and ambient temperature. The high heritability estimates and genetic correlations for rumen and rectal temperature parameters demonstrate their potential as beef genetic improvement tools of economic traits associated with the parameters. However, there are limited practical implications of using only the core-body temperature as a proxy for production efficiency traits for beef steers during winter.
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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 | 0.000 | 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 | 0.000 |
| 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".