PSXII-24 Examining Relationships Between Residual Feed Intake Classification, Enteric Emissions, and Apparent Total Tract Digestibility in Late Gestation Beef Heifers
Bibliographic record
Abstract
Abstract Improving feed efficiency on forage-based systems can be an important tool for beef producers to reduce their environmental footprint. The objective of this project is to assess the relationship between traditional residual feed intake (RFI) efficiency classification, enteric gas emissions, and apparent total tract nutrient digestibility in late gestation beef heifers. Pregnant Angus crossbred heifers in late gestation (n = 72, BW = 576 ± 45.8 kg) were blocked by expected calving date and randomly assigned to pen groups. Heifers had ad libitum access to a common haylage-based diet formulated to meet nutritional requirements for the last eight weeks of gestation. Individual feed intake and behavior data were recorded daily using Insentec feeding stations (Insentec B.V., Marknesse, The Netherlands). Groups of heifers were rotated through pens with access to GreenFeed trailers (C-Lock Inc., Rapid City, SD, USA) to measure enteric gas emissions of methane (CH4), carbon dioxide (CO2), and oxygen (O2). To determine individual apparent total tract digestibility, fecal samples were collected from each heifer every 9 h over three days, mixed, dried at 65 °C for 96 h, and analyzed for nutrient values (A&L Canada Laboratories, London, ON, Canada). Nutrient digestibility was determined for each heifer using acid-insoluble ash (AIA) and undigestible neutral detergent fiber (uNDF) as internal markers. Heifer RFI was determined using predicted DM intake as a regression of midpoint BW and ADG, and heifers were classified by RFI quartile group. Data were analyzed using PROC GLIMMIX in SAS, with efficiency quartile group as the fixed effect and pen as a random effect, comparisons between quartile groups were assessed with a Tukey test. Heifers classified as efficient (lowest RFI) had decreased DMI (8.2 vs 10.7 ± 0.21 kg/d, P < 0.01), less bunk visits (43 vs 64 ± 5 visits/day, P < 0.01) and greater time per visit (4.8 vs 3.0 ± 0.53 min/visit, P = 0.05). Efficient heifers also had reduced CH4 (219 vs 245 ± 6.2 g/d, P = 0.03) and CO2 (7,517 vs 8,074 ± 165.9 g/d, P = 0.01) emissions compared with inefficient (greatest RFI) heifers. However, apparent total tract digestibility of organic matter, crude protein, NDF, ADF, starch, and sugar using AIA (P > 0.08) or uNDF (P > 0.06) as internal markers were not correlated with heifer efficiency. These data indicate that more efficient heifers in late gestation consume less feed and have reduced enteric emissions, despite no differences in apparent total tract digestibility.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".