Use of remote bunk monitoring to record effects of breed, feeding regime and weather on feeding behavior and growth performance of cattle
Bibliographic record
Abstract
Thirty Charolais and 29 Holstein steers (432 ± 30 kg) blocked by weight and breed were randomly assigned to four feedlot pens equipped with radio frequency identification systems in the feed bunks. The systems monitored individual steers’ bunk attendance patterns (time, frequency, and duration of visits). Over four 21-d periods, the steers were offered (two times per day) an 80% barley grain: 20% barley silage diet for ad libitum intake (AL); restricted to 95% of their dry matter intake (DMI); during the previous 21 d; returned to an AL regime for 21 d; then restricted once again (RF). Weather data (air temperature, AT; relative humidity, RH; barometric pressure, BP; and wind speed, (WS) were expected at 1-h intervals throughout the four periods. Steer weights were recorded every 21 d; feed refusals every 7 d. Charolais steers had lower DMI (P < 0.05), higher (P < 0.005) average daily gain (ADG) and were more (P < 0.05) efficient than Holstein steers. Higher daily bunk attendance was recorded for Holstein steers during RF (P < 0.0001), and lowest for Charolais steers during RF (P < 0.0001). Dry matter intake, ADG and feed conversion were higher (v < 0.05) with AL than; with RF. Effects of weather varied with feeding regime and breed. On the AL regime, Charolais steers exhibited larger variation in daily bunk attendance than Holsteins (P < 0.0001) in relation to weather categories AT, RH and BP, but this did not compromise growth performance. Long-term data collection is required to relate the impact of weather on feeding patterns of feedlot cattle over different seasons and in different geographic locations. Key words: Feeding behaviour, feedlot, performance, thermal environment, radio frequency
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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".