Residual feed intake and body composition in young growing cattle
Bibliographic record
Abstract
Crossbred steers (n = 176), 7–8 mo of age and from the five BeefBooster strains (M1, M2, M3, M4 and TX), were used to determine the relationships between residual feed intake (RFI) and growth rate, body composition and heat production (HP), and to quantify differences in RFI independent of differences in body composition. Animals with different RFI levels were also characterized for growth, carcass and body compositional traits. Steers from each genetic strain were selected at random and serially slaughtered on 5 pre-selected days of the finishing period. Steers grew at 1.52 (SD = 0.22) kg d -1 and had dry matter intake (DMI) of 8.5 (SD = 1.0) kg d -1 during the last 71 to 183 d before slaughter. Metabolic mid-point weight, average daily gain (ADG), gain in empty body fat and gain in empty body water accounted for 67.9, 8.6, 3.9 and 1.1%, respectively, of the variation in actual feed intake. Similarly, metabolic mid-point weight (68.5%), ADG (8.2%), gain in ultrasound backfat thickness (1.8%), gain in ultrasound marbling score (1.1%) and year (1.3%) accounted for 80.9% of the variation in actual feed intake. Residual feed intake adjusted for differences in estimated composition of gain (estimated gain in empty body fat and water; RFI II ) ranged from -2.06 kg d -1 to +1.61 kg d -1 (SD = 0.60 kg d -1 ). Residual feed intake adjusted for live animal measures of body composition (gain in ultrasound backfat thickness and marbling score; RFI III ) ranged from -2.11 kg d -1 to +1.88 kg d -1 (SD = 0.62 kg d -1 ). Low RFI III animals (efficient) had 6.0% lower metabolizable energy intake (MEI), retained 9.3% less energy and had 4.5% lower HP than medium RFI III animals (P < 0.01). Low RFI III animals also had 10.2% lower MEI, retained 12.0% less energy and produced 9.3% less heat than high RFI III animals (P < 0.01). Liver (P <0.01), small and large intestine (P = 0.09) and stomach and intestine (P < 0.01) weights were less in low and medium RFI III steers compared to high RFI III steers. There was a trend for low RFI III steers to have less dissectible carcass fat (P = 0.08), intermuscular fat (P = 0.06), body cavity fat in the butt and loin (P = 0.01), faster accretion rate of empty body water (P = 0.04) and a slower accretion rate of empty body fat (P < 0.01) than medium and high RFI III steers. A portion of the greater MEI by high RFI III steer was accounted for by differences in the chemical composition of gain. However, a greater proportion was due to a disproportionate increase in the energy required for maintenance and heat increment of feeding in high RFI III steers. An attempt should be made to adjust RFI for changes in the chemical composition of gain, possibly by the inclusion of ultrasound backfat thickness and marbling score into the equation for determining RFI. Key words: Cattle, feed efficiency, residual feed intake, remote sensing, GrowSafe System
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".