Growth and physiological responses of growing pigs to wheat–corn distillers dried grains with solubles
Bibliographic record
Abstract
Gaining a detailed knowledge on the impact of a feedstuff on pig growth and physiological responses is critical for its effective utilization. Thus, the purpose of this study was to investigate the effect of distillers dried grains with solubles derived from co-fermentation of wheat and corn (wcDDGS) on performance, carcass and visceral organ weights, whole-body O2 consumption and heat production (HP) in growing barrows. The experimental diets were as follows: corn-soybean meal diet (Control), Control + 15% wcDDGS and Control + 30% wcDDGS. In Exp. 1, 48 pair-housed pigs of average BW 18.6 ± 1.5 kg (mean ± SD) were allotted to the 3 diets (n = 8). Pigs had free access to water and feed for a 28-day period during which ADG and ADFI were calculated weekly. Thereafter, 1 pig/pen was killed to measure carcass and visceral organ weights. Overall, wcDDGS linearly decreased (p < 0.05) ADFI and ADG but had no effect on G:F (p > 0.10). The ADFI was 1.55, 1.45 and 1.36 kg/day for diets containing 0, 15 and 30% wcDDGS respectively; corresponding values for ADG were 0.79, 0.75 and 0.67 kg/day respectively. A linear decline (p = 0.01) in eviscerated hot carcass weight was observed as dietary wcDDGS increased. In Exp. 2, 18 pigs of average BW 20.4 ± 2.4 kg (mean ± SD) were individually housed in metabolism crates and fed the 3 diets (n = 6) at 550 kcal ME kg BW(-0.60) day for a 16-day period followed by measurement of O2 consumption using an indirect calorimeter. Diet had no effect (p > 0.10) on whole-body O2 consumption and HP. In conclusion, increasing wcDDGS content in growing pig diets linearly reduced ADFI, ADG and eviscerated hot carcass weight but had no effect on G:F, visceral organ weights or HP.
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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 | 0.000 |
| 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 | 0.001 |
| 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".