Greenhouse gases and performance of growing pigs fed wheat-based diets containing wheat millrun and a multi-carbohydrase enzyme
Bibliographic record
Abstract
The objective of this project was to determine the impact of feeding growing pigs with high wheat millrun diets supplemented with a multi-carbohydrase enzyme (amylase, cellulase, glucanase, xylanase, and invertase activities) on nutrient digestibility, growth performance, and greenhouse gas (GHG) output (carbon dioxide, CO2; nitrous oxide, N2O; methane, CH4). Three experiments were conducted utilizing six treatments arranged as a 3 × 2 factorial (0%, 15%, or 30% wheat millrun; with or without enzyme) for the digestibility experiment or as a 2 × 2 factorial (0% or 30% wheat millrun; with or without enzyme) for the performance and GHG experiments. The digestibility, performance, and GHG experiments utilized 48 individually housed pigs, 180 pigs housed 5 per pen, or 96 pigs housed 6 per chamber, respectively. Increasing wheat millrun up to 30% in the diet of growing pigs resulted in decreased energy, nitrogen (N) and phosphorus (P) apparent total tract digestibility and net energy content (P < 0.01). Overall, average daily gain (ADG) and gain to feed ratio were reduced in pigs fed wheat millrun (P < 0.05). Enzyme supplementation had minimal effects on the digestibility or performance parameters measured. Feeding diets with 30% millrun did not affect GHG output (CH4: 4.7 and 4.9; N2O: 0.45 and 0.42; CO2: 1,610 and 1,711 mg/s without or with millrun inclusion, respectively; P > 0.78). Enzyme supplementation had no effect on GHG emissions (CH4: 4.5 and 5.1; N2O: 0.46 and 0.42; CO2: 1,808 and 1,513 mg/s without or with enzymes, respectively; P > 0.51). Overall, the carbohydrase enzyme had minimal effects on parameters measured, regardless of wheat millrun inclusion (P > 0.10). Although energy, N and P digestibility, and ADG were reduced, the inclusion of up to 30% wheat millrun in the diet has no effect on GHG emissions from growing pigs (P > 0.10).
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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".